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28 results on '"Sylvain Lefebvre"'

1. Anisotropic Soft Robots Based on 3D Printed Meso-Structured Materials: Design, Modeling by Homogenization and Simulation

Author

Olivier Goury, Jonàs Martínez, Hervé Delingette, Christian Duriez, Sylvain Lefebvre, Felix Vanneste, Deformable Robots Simulation Team (DEFROST ), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Geometry and Lighting (ALICE), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Matter from Graphics (MFX), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), Hauts de France Region, SOFA, ANR-17-CE10-0002,MuFFin,Microstructures procedurales et stochastiques pour la fabrication fonctionnelle(2017), Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 (CRIStAL), Ecole Centrale de Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 (CRIStAL), Ecole Centrale de Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Ecole Centrale de Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université Côte d'Azur (UCA), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Inria Nancy - Grand Est, and Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
0209 industrial biotechnology, 3d printed, Kinematics, Control and Optimization, Computer science, Additive Manufacturing, Simulation and Animation, Biomedical Engineering, Mechanical engineering, 02 engineering and technology, Materials design, Homogenization (chemistry), 020901 industrial engineering & automation, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, medicine, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Anisotropy, ComputingMethodologies_COMPUTERGRAPHICS, Mechanical Engineering, Stiffness, 020207 software engineering, Soft Robot Applications, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Finite element method, Computer Science Applications, Human-Computer Interaction, Control and Systems Engineering, Robot, Computer Vision and Pattern Recognition, medicine.symptom, Soft Robot Materials and Design
Abstract

International audience; In this paper, we propose to use new 3D-printed meso-structured materials to build soft robots and we present a modeling pipeline for design assistance and control. These meta-materials can be programmed before printing to target specific mechanical properties, in particular heterogeneous stiffness and anisotropic behaviour. Without changing the external shape, we show that using such meta-material can lead to a dramatic change in the kinematics of the robot. This highlights the importance of modeling. Therefore, to help the design and to control soft robots made of these meso-structured materials, we present a modeling method based on numerical homogenization and Finite Element Method (FEM) that captures the anisotropic deformations. The method is tested on a 3 axis parallel soft robot initially made of silicone. We demonstrate the change in kinematics when the robot is built with meso-structured materials and compare its behavior with modeling results.

Published
2020
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2. AI in the media and creative industries

Author

Baptiste Caramiaux, Fabien Lotte, Joost Geurts, Giuseppe Amato, Malte Behrmann, Frédéric Bimbot, Fabrizio Falchi, Ander Garcia, Jaume Gibert, Guillaume Gravier, Hadmut Holken, Hartmut Koenitz, Sylvain Lefebvre, Antoine Liutkus, Andrew Perkis, Rafael Redondo, Enrico Turrin, Thierry Viéville, Emmanuel Vincent, Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Extreme Interaction (EX-SITU), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Popular interaction with 3d content (Potioc), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), Direction des Partenariats Européens et Internationaux (DPEI), Institut National de Recherche en Informatique et en Automatique (Inria), Consiglio Nazionale delle Ricerche [Pisa] (CNR PISA), bbw Hochschule, Parcimonie et Nouveaux Algorithmes pour le Signal et la Modélisation Audio (PANAMA), SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Inria Rennes – Bretagne Atlantique, VicomTech, Eurecat - Centro Tecnológico de Catalunya, Creating and exploiting explicit links between multimedia fragments (LinkMedia), MEDIA ET INTERACTIONS (IRISA-D6), Holken Consultants, University of the Arts Utrecht (HKU), Matter from Graphics (MFX), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Inria Nancy - Grand Est, Scientific Data Management (ZENITH), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Inria Sophia Antipolis - Méditerranée (CRISAM), Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Federation of European Publishers (FEP), Mnemonic Synergy (Mnemosyne), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), New European Media (NEM), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Inria Siège, Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-MEDIA ET INTERACTIONS (IRISA-D6), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CentraleSupélec-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-Inria Rennes – Bretagne Atlantique, Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Nancy - Grand Est, Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), CentraleSupélec-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), CentraleSupélec-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1)

Subjects
Media, [SHS.INFO]Humanities and Social Sciences/Library and information sciences, Inclusivity, News, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], GeneralLiterature_MISCELLANEOUS, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Video games, Creativity, [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Artificial Intelligence, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], Diversity, Creative Economy, [SHS.ARCHI]Humanities and Social Sciences/Architecture, space management, [SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts, Personalization, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-IA]Computer Science [cs]/Computer Aided Engineering, [SHS.ART]Humanities and Social Sciences/Art and art history, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, Sound, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Open Society, [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD], [INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET], Music, Design
Abstract

Thanks to the Big Data revolution and increasing computing capacities, Artificial Intelligence (AI) has made an impressive revival over the past few years and is now omnipresent in both research and industry. The creative sectors have always been early adopters of AI technologies and this continues to be the case. As a matter of fact, recent technological developments keep pushing the boundaries of intelligent systems in creative applications: the critically acclaimed movie “Sunspring”, released in 2016, was entirely written by AI technology, and the first-ever Music Album, called “Hello World”, produced using AI has been released this year. Simultaneously, the exploratory nature of the creative process is raising important technical challenges for AI such as the ability for AI-powered techniques to be accurate under limited data resources, as opposed to the conventional “Big Data” approach, or the ability to process, analyse and match data from multiple modalities (text, sound, images, etc.) at the same time. The purpose of this white paper is to understand future technological advances in AI and their growing impact on creative industries. This paper addresses the following questions: Where does AI operate in creative Industries? What is its operative role? How will AI transform creative industries in the next ten years? This white paper aims to provide a realistic perspective of the scope of AI actions in creative industries, proposes a vision of how this technology could contribute to research and development works in such context, and identifies research and development challenges.

Published
2019

3. Collaborative Clustering through Constrained Networks using Bandit Optimization

Author

Sylvain Lefebvre and Jérémie Sublime

Subjects
Distributed database, business.industry, Computer science, 02 engineering and technology, 010501 environmental sciences, Machine learning, computer.software_genre, 01 natural sciences, 0202 electrical engineering, electronic engineering, information engineering, Entropy (information theory), 020201 artificial intelligence & image processing, Artificial intelligence, Cluster analysis, business, computer, 0105 earth and related environmental sciences
Abstract

Collaborative clustering is a machine learning paradigm concerned with the unsupervised analysis of complex multi-view data using several algorithms working together. Well known applications of collaborative clustering include multiview clustering and distributed data clustering, where several algorithms exchange information in order to mutually improve each others. One of the key issue with multi-view and collaborative clustering is to assess which collaborations are going to be beneficial or detrimental. Many solutions have been proposed for this problem, and all of them conclude that unless two models are very close, it is difficult to predict in advance the result of a collaboration. To alleviate this problem, in this paper we propose a collaborative peer to peer clustering algorithm based on the principle of non stochastic multi-arm bandits to assess in real time which algorithms or views can bring useful information. Our method has been evaluated on several datasets with extensive experiments that demonstrate its effectiveness.

Published
2018
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4. Colored fused filament fabrication

Author

Pierre Bedell, Sylvain Lefebvre, Noémie Vennin, Haichuan Song, Jonàs Martínez, Géometrie et Lumière (ALICE-POST), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Matter from Graphics (MFX), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Nancy - Grand Est

Subjects
Computational Geometry (cs.CG), FOS: Computer and information sciences, 0209 industrial biotechnology, Computer science, business.industry, Property (programming), Base (geometry), ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 3D printing, 020207 software engineering, Fused filament fabrication, 02 engineering and technology, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], Computer Graphics and Computer-Aided Design, 020901 industrial engineering & automation, Colored, Color mixing, 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Computational Geometry, Computer vision, Dither, Artificial intelligence, business
Abstract

Fused filament fabrication is the method of choice for printing 3D models at low cost and is the de facto standard for hobbyists, makers, and schools. Unfortunately, filament printers cannot truly reproduce colored objects. The best current techniques rely on a form of dithering exploiting occlusion, which was only demonstrated for shades of two base colors and behaves differently depending on surface slope. We explore a novel approach for 3D-printing colored objects, capable of creating controlled gradients of varying sharpness. Our technique exploits off-the-shelf nozzles that are designed to mix multiple filaments in a small melting chamber, obtaining intermediate colors once the mix is stabilized. We apply this property to produce color gradients. We divide each input layer into a set of strata, each having a different constant color. By locally changing the thickness of the stratum, we change the perceived color at a given location. By optimizing the choice of colors of each stratum, we further improve quality and allow the use of different numbers of input filaments. We demonstrate our results by building a functional color printer using low-cost, off-the-shelf components. Using our tool, a user can paint a 3D model and directly produce its physical counterpart using any material and color available for fused filament fabrication.

Published
2017
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5. Rethinking texture mapping

Author

Marco Tarini, Cem Yuksel, and Sylvain Lefebvre

Subjects
Tile trees, Computer science, business.industry, Mesh Colors, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020207 software engineering, 02 engineering and technology, Computer Graphics and Computer-Aided Design, Course (navigation), Volume Encoded UV maps, Software, 1707, Computer graphics (images), UV mapping, 0202 electrical engineering, electronic engineering, information engineering, PTex, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Texture mapping, Texture Mapping
Abstract

The intrinsic problems of standard Texture Mapping, regarding UV-maps and seams, are well-known, but often considered unavoidable. In this course we will discuss various radically different ways to rethink texture mapping that have been proposed over decades, each offering different advantages and trade-offs.

Published
2017

6. Bridges between multiple-point geostatistics and texture synthesis: Review and guidelines for future research

Author

Gregoire Mariethoz and Sylvain Lefebvre

Subjects
Computer science, business.industry, 020207 software engineering, 02 engineering and technology, Geostatistics, 010502 geochemistry & geophysics, Machine learning, computer.software_genre, 01 natural sciences, Texture (geology), Field (geography), Computer graphics, User control, 0202 electrical engineering, electronic engineering, information engineering, Spatial variability, Artificial intelligence, Computers in Earth Sciences, business, Spatial analysis, computer, 0105 earth and related environmental sciences, Information Systems, Texture synthesis
Abstract

Multiple-Point Simulations (MPS) is a family of geostatistical tools that has received a lot of attention in recent years for the characterization of spatial phenomena in geosciences. It relies on the definition of training images to represent a given type of spatial variability, or texture. We show that the algorithmic tools used are similar in many ways to techniques developed in computer graphics, where there is a need to generate large amounts of realistic textures for applications such as video games and animated movies. Similarly to MPS, these texture synthesis methods use training images, or exemplars, to generate realistic-looking graphical textures.Both domains of multiple-point geostatistics and example-based texture synthesis present similarities in their historic development and share similar concepts. These disciplines have however remained separated, and as a result significant algorithmic innovations in each discipline have not been universally adopted. Texture synthesis algorithms present drastically increased computational efficiency, patterns reproduction and user control. At the same time, MPS developed ways to condition models to spatial data and to produce 3D stochastic realizations, which have not been thoroughly investigated in the field of texture synthesis.In this paper we review the possible links between these disciplines and show the potential and limitations of using concepts and approaches from texture synthesis in MPS. We also provide guidelines on how recent developments could benefit both fields of research, and what challenges remain open. We provide a comparative historical overview of MPS and texture synthesis.Some concepts that were thought as original in geostatistics have actually been used for a long time in computer graphics.We analyze the considerable computational gains that were achieved in texture synthesis in the last decades.Recommendations are given regarding future research directions and potential cross-fertilization between disciplines.

Published
2014
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7. Session details: Texture

Author

Sylvain Lefebvre

Subjects
business.industry, Computer science, Computer vision, Session (computer science), Artificial intelligence, business, Computer Graphics and Computer-Aided Design, Texture (geology)
Published
2016
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8. Synthesis of Filigrees for Digital Fabrication

Author

Wenping Wang, Yang Xia, Sylvain Lefebvre, Xiaolong Zhang, Shiqing Xin, Weikai Chen, The University of Hong Kong (HKU), University of Nottingham Ningbo [China], Dalian University of Technology, Geometry and Lighting (ALICE), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), European Project: 307877,EC:FP7:ERC,ERC-2012-StG_20111012,SHAPEFORGE(2012), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)

Subjects
Matching (graph theory), Computer science, digital fabrication, 02 engineering and technology, medial axis, Set (abstract data type), 0202 electrical engineering, electronic engineering, information engineering, Computer vision, and object modeling, filigree synthesis, Orientation (computer vision), business.industry, Hausdorff distance, Process (computing), 020207 software engineering, Ornaments, Object (computer science), Base (topology), Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], 020201 artificial intelligence & image processing, Artificial intelligence, Physically based modeling, business, Concepts: •Computer graphics → Computational geometry, Algorithm
Abstract

Filigrees are thin patterns found in jewelry, ornaments and lace fabrics. They are often formed of repeated base elements manually composed into larger, delicate patterns. Digital fabrication simplifies the process of turning a virtual model of a filigree into a physical object. However, designing a virtual model of a filigree remains a time consuming and challenging task. The difficulty lies in tightly packing together the base elements while covering a target surface. In addition, the filigree has to be well connected and sufficiently robust to be fabricated. We propose a novel approach automating this task. Our technique covers a target surface with a set of input base elements, forming a filigree strong enough to be fabricated. We exploit two properties of filigrees to make this possible. First, as filigrees form delicate traceries they are well captured by their skeleton. This affords for a simpler definition of operators such as matching and deformation. Second, instead of seeking for a perfect packing of the base elements we relax the problem by allowing appearance preserving partial overlaps. We optimize a filigree by a stochastic search, further improved by a novel boosting algorithm that records and reuses good configurations discovered during the process. We illustrate our technique on a number of challenging examples reproducing filigrees on large objects, which we manufacture by 3D printing. Our technique affords for several user controls, such as the scale and orientation of the elements.

Published
2016
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9. Procedural texture preview

Author

Anass Lasram, Sylvain Lefebvre, Cyrille Damez, Geometry and Lighting (ALICE), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Allegorithmic, Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Nancy - Grand Est, and Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Pixel, Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 0211 other engineering and technologies, Thumbnail, 020207 software engineering, 02 engineering and technology, Space (commercial competition), Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Image (mathematics), Computer graphics (images), 0202 electrical engineering, electronic engineering, information engineering, Procedural texture, Computer vision, Shading, Artificial intelligence, business, ComputingMethodologies_COMPUTERGRAPHICS, 021106 design practice & management, Texture synthesis
Abstract

Procedural textures usually require spending time testing parameters to realize the diversity of appearances. This paper introduces the idea of a procedural texture preview: A single static image summarizing in a limited pixel space the appearances produced by a given procedure. Unlike grids of thumbnails our previews present a continuous image of appearances, analog to a map. The main challenge is to ensure that most appearances are visible, are allocated a similar pixel area, and are ordered in a smooth manner throughout the preview. To reach this goal, we introduce a new layout algorithm accounting simultaneously for these criteria. After computing a layout of appearances, we rely on by-example texture synthesis to produce the final preview. We demonstrate our approach on a database of production-level procedural textures. © 2012 Wiley Periodicals, Inc.

Published
2012
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10. A Survey of Procedural Noise Functions

Author

John P. Lewis, Robert L. Cook, Matthias Zwicker, Ken Perlin, Ares Lagae, Tony DeRose, Sylvain Lefebvre, George Drettakis, David S. Ebert, Department of Computer Science [Leuven] (CS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Geometry and Lighting (ALICE), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria), Pixar Animation Studios, School of Electrical and Computer Engineering [West Lafayette] (ECE), Purdue University [West Lafayette], Weta Digital, Weta, Courant Institute of Mathematical Sciences [New York] (CIMS), New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), Universität Bern [Bern], Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), and Universität Bern [Bern] (UNIBE)

Subjects
Computer science, Interactive video, business.industry, 020207 software engineering, 02 engineering and technology, Filter (signal processing), Anti-aliasing, Computer Graphics and Computer-Aided Design, Data science, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Rendering (computer graphics), Computer graphics, Wavelet noise, 0202 electrical engineering, electronic engineering, information engineering, Procedural texture, 020201 artificial intelligence & image processing, Artificial intelligence, Graphics, Perlin noise, business, Texture synthesis
Abstract

Procedural noise functions are widely used in Computer Graphics, from off-line rendering in movie production to interactive video games. The ability to add complex and intricate details at low memory and authoring cost is one of its main attractions. This survey is motivated by the inherent importance of noise in graphics, the widespread use of noise in industry, and the fact that many recent research developments justify the need for an up-to-date survey. Our goal is to provide both a valuable entry point into the field of procedural noise functions, as well as a comprehensive view of the field to the informed reader. In this report, we cover procedural noise functions in all their aspects. We outline recent advances in research on this topic, discussing and comparing recent and well established methods. We first formally define procedural noise functions based on stochastic processes and then classify and review existing procedural noise functions. We discuss how procedural noise functions are used for modeling and how they are applied to surfaces. We then introduce analysis tools and apply them to evaluate and compare the major approaches to noise generation. We finally identify several directions for future work. ispartof: Computer Graphics Forum vol:29 issue:8 pages:2579-2600 status: published

Published
2010
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11. Structure-Preserving Reshape for Textured Architectural Scenes

Author

Sylvain Lefebvre, Marcio Cabral, Carsten Dachsbacher, George Drettakis, Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut für Visualisierung und Interaktive Systeme [Stuttgart] (VIS), and Universität Stuttgart [Stuttgart]

Subjects
Structure (mathematical logic), ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.3: Picture/Image Generation/I.3.3.4: Line and curve generation, Computer science, business.industry, Orientation (computer vision), Computer Graphics and Computer-Aided Design, Texture (geology), [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Architectural geometry, Simple (abstract algebra), Computer graphics (images), Key (cryptography), Geometric primitive, Computer vision, Artificial intelligence, business, Focus (optics), ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; Modeling large architectural environments is a difficult task due to the intricate nature of these models and the complex dependencies between the structures represented. Moreover, textures are an essential part of architectural models. While the number of geometric primitives is usually relatively low (i.e., many walls are flat surfaces), textures actually contain many detailed architectural elements. We present an approach for modeling architectural scenes by reshaping and combining existing textured models, where the manipulation of the geometry and texture are tightly coupled. For geometry, preserving angles such as floor orientation or vertical walls is of key importance. We thus allow the user to interactively modify lengths of edges, while constraining angles. Our texture reshaping solution introduces a measure of directional autosimilarity, to focus stretching in areas of stochastic content and to preserve details in such areas. We show results on several challenging models, and show two applications: Building complex road structures from simple initial pieces and creating complex game-levels from an existing game based on pre-existing model pieces.

Published
2009
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12. Texture Synthesis From Photographs

Author

Christian Eisenacher, Marc Stamminger, Sylvain Lefebvre, Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Erlangen], and Friedrich-Alexander Universität Erlangen-Nürnberg (FAU)

Subjects
Texture atlas, Projective texture mapping, Texture compression, Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Computer Graphics and Computer-Aided Design, Texture (geology), [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Image texture, Texture filtering, Distortion, Computer graphics (images), Computer vision, Artificial intelligence, Bidirectional texture function, business, Texel, ComputingMethodologies_COMPUTERGRAPHICS, Texture synthesis
Abstract

International audience; The goal of texture synthesis is to generate an arbitrarily large high-quality texture from a small input sample. Generally, it is assumed that the input image is given as a flat, square piece of texture, thus it has to be carefully prepared from a picture taken under ideal conditions. Instead we would like to extract the input texture from any surface from within an arbitrary photograph. This introduces several challenges: Only parts of the photograph are covered with the texture of interest, perspective and scene geometry introduce distortions, and the texture is non-uniformly sampled during the capture process. This breaks many of the assumptions used for synthesis. In this paper we combine a simple novel user interface with a generic per-pixel synthesis algorithm to achieve high-quality synthesis from a photograph. Our interface lets the user locally describe the geometry supporting the textures by combining rational Bézier patches. These are particularly well suited to describe curved surfaces under projection. Further, we extend per-pixel synthesis to account for arbitrary texture sparsity and distortion, both in the input image and in the synthesis output. Applications range from synthesizing textures directly from photographs to high-quality texture completion.

Published
2008
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13. Structure and appearance optimization for controllable shape design

Author

Li-Yi Wei, Jonàs Martínez, Sylvain Lefebvre, Jérémie Dumas, Geometry and Lighting (ALICE), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université de Lorraine (UL), The University of Hong Kong (HKU), European Project: 307877,EC:FP7:ERC,ERC-2012-StG_20111012,SHAPEFORGE(2012), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Inria Nancy - Grand Est

Subjects
Shape design, Computer science, business.industry, Topology optimization, modeling, [SPI.MECA]Engineering Sciences [physics]/Mechanics [physics.med-ph], Computer Graphics and Computer-Aided Design, texture synthesis, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], manufacturing, Computer vision, [INFO]Computer Science [cs], Artificial intelligence, business, Algorithm, topology optimization, Texture synthesis, Shape analysis (digital geometry)
Abstract

The field of topology optimization seeks to optimize shapes under structural objectives, such as achieving the most rigid shape using a given quantity of material. Besides optimal shape design, these methods are increasingly popular as design tools, since they automatically produce structures having desirable physical properties, a task hard to perform by hand even for skilled designers. However, there is no simple way to control the appearance of the generated objects. In this paper, we propose to optimize shapes for both their structural properties and their appearance, the latter being controlled by a user-provided pattern example. These two objectives are challenging to combine, as optimal structural properties fully define the shape, leaving no degrees of freedom for appearance. We propose a new formulation where appearance is optimized as an objective while structural properties serve as constraints. This produces shapes with sufficient rigidity while allowing enough freedom for the appearance of the final structure to resemble the input exemplar. Our approach generates rigid shapes using a specified quantity of material while observing optional constraints such as voids, fills, attachment points, and external forces. The appearance is defined by examples, making our technique accessible to casual users. We demonstrate its use in the context of fabrication using a laser cutter to manufacture real objects from optimized shapes.

Published
2015
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14. Appearance-space texture synthesis

Author

Sylvain Lefebvre and Hugues Hoppe

Subjects
Pointwise, business.industry, Atlas (topology), Dimensionality reduction, Texton, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Space (mathematics), Computer Graphics and Computer-Aided Design, Feature (computer vision), Texture advection, Computer vision, Artificial intelligence, business, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics, Texture synthesis
Abstract

The traditional approach in texture synthesis is to compare color neighborhoods with those of an exemplar. We show that quality is greatly improved if pointwise colors are replaced by appearance vectors that incorporate nonlocal information such as feature and radiance-transfer data. We perform dimensionality reduction on these vectors prior to synthesis, to create a new appearance-space exemplar. Unlike a texton space, our appearance space is low-dimensional and Euclidean. Synthesis in this information-rich space lets us reduce runtime neighborhood vectors from 5x5 grids to just 4 locations. Building on this unifying framework, we introduce novel techniques for coherent anisometric synthesis, surface texture synthesis directly in an ordinary atlas, and texture advection. Remarkably, we achieve all these functionalities in real-time, or 3 to 4 orders of magnitude faster than prior work.

Published
2006
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15. Gabor noise by example

Author

Bruno Galerne, Sylvain Lefebvre, Ares Lagae, George Drettakis, Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Leuven] (CS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Geometry and Lighting (ALICE), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), KU Leuven project CREA/08/017, and European Project: 288914,EC:FP7:ICT,FP7-ICT-2011-7,VERVE(2011)

Subjects
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Gabor transform, symbols.namesake, 0202 electrical engineering, electronic engineering, information engineering, Value noise, Mathematics, Noise measurement, business.industry, Gabor wavelet, 020207 software engineering, Pattern recognition, Computer Graphics and Computer-Aided Design, Gaussian random field, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], non-negative basis pursuit denoising, Gradient noise, Noise, ComputingMethodologies_PATTERNRECOGNITION, Gaussian noise, decorrelated color space, Computer Science::Computer Vision and Pattern Recognition, symbols, procedural noise, 020201 artificial intelligence & image processing, Gabor–Wigner transform, Artificial intelligence, business, power spectrum estimation, Gaussian texture
Abstract

Procedural noise is a fundamental tool in Computer Graphics. However, designing noise patterns is hard. In this paper, we present Gabor noise by example, a method to estimate the parameters of bandwidth-quantized Gabor noise, a procedural noise function that can generate noise with an arbitrary power spectrum, from exemplar Gaussian textures, a class of textures that is completely characterized by their power spectrum. More specifically, we introduce (i) bandwidth-quantized Gabor noise, a generalization of Gabor noise to arbitrary power spectra that enables robust parameter estimation and efficient procedural evaluation; (ii) a robust parameter estimation technique for quantized-bandwidth Gabor noise, that automatically decomposes the noisy power spectrum estimate of an exemplar into a sparse sum of Gaussians using non-negative basis pursuit denoising; and (iii) an efficient procedural evaluation scheme for bandwidth-quantized Gabor noise, that uses multi-grid evaluation and importance sampling of the kernel parameters. Gabor noise by example preserves the traditional advantages of procedural noise, including a compact representation and a fast on-the-fly evaluation, and is mathematically well-founded. ispartof: ACM Transactions on Graphics vol:31 issue:4 pages:73-73 ispartof: SIGGRAPH edition:2012 location:Los Angeles, USA date:5-9 August 2012 status: published

Published
2012
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16. Improving Gabor Noise

Author

P. Dutre, Sylvain Lefebvre, Ares Lagae, Department of Computer Science [Leuven] (CS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Geometry and Lighting (ALICE), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Gabor transform, Convolution, Harmonic analysis, symbols.namesake, 0202 electrical engineering, electronic engineering, information engineering, Value noise, Mathematics::Functional Analysis, Hankel transform, Noise measurement, business.industry, Gabor wavelet, 020207 software engineering, Pattern recognition, Salt-and-pepper noise, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Gradient noise, Noise, ComputingMethodologies_PATTERNRECOGNITION, Gaussian noise, Colors of noise, Computer Science::Sound, Frequency domain, Computer Science::Computer Vision and Pattern Recognition, Signal Processing, symbols, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, business, Software
Abstract

We have recently proposed a new procedural noise function, Gabor noise, which offers a combination of properties not found in existing noise functions. In this paper, we present three significant improvements to Gabor noise: (1) an isotropic kernel for Gabor noise, which speeds up isotropic Gabor noise with a factor of roughly two, (2) an error analysis of Gabor noise, which relates the kernel truncation radius to the relative error of the noise, and (3) spatially varying Gabor noise, which enables spatial variation of all noise parameters. These improvements make Gabor noise an even more attractive alternative for existing noise functions. ispartof: IEEE Transactions on Visualization and Computer Graphics vol:17 issue:8 pages:1096-1107 ispartof: location:United States status: published

Published
2011
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17. Assisted Texture Assignment

Author

Sylvain Lefebvre, Marc Stamminger, Matthäus G. Chajdas, Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Erlangen], Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Geometry and Lighting (ALICE), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), and Lefebvre, Sylvain

Subjects
Surface (mathematics), Texture atlas, Computer science, Event (computing), business.industry, Process (computing), [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020207 software engineering, 02 engineering and technology, Similarity measure, Measure (mathematics), [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Ranking (information retrieval), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Texture mapping, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; Virtual environments are typically textured by manually choosing an image to apply on each surface. This implies browsing through large sets of generic textures for each and every surface in the scene. We propose to facilitate this long and tedious process. Our algorithm assists the user while he assigns textures to surfaces. Each time an image is chosen for a surface, our algorithm propagates this information throughout the entire environment. Our approach is based on a new surface similarity measure. We exploit this measure in an algorithm ranking all possible textures for a given surface. Hence, we do not simply assign a texture to the surface but also propose an ordered list of choices for the user. In the unavoidable event of an ambiguous choice, the user can quickly make a decision and select the best texture. Our algorithm is fast enough to allow for interactive feedback. Applications range from assisted interactive texturing to fully automatic initial texturing solutions.

Published
2011

18. Relighting Photographs of Tree Canopies

Author

Sylvain Lefebvre, George Drettakis, Marcio Cabral, Nicolas Bonneel, Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Computer Science Department (UBC-Computer Science), and University of British Columbia (UBC)

Subjects
Image based rendering, Computer science, media_common.quotation_subject, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, relighting, 02 engineering and technology, Volumetric lighting, GeneralLiterature_MISCELLANEOUS, Rendering (computer graphics), Computer graphics (images), 0202 electrical engineering, electronic engineering, information engineering, Computer vision, media_common, ComputingMethodologies_COMPUTERGRAPHICS, Ground truth, Tree canopy, Pixel, business.industry, Spherical harmonics, 020207 software engineering, Image-based modeling and rendering, Computer Graphics and Computer-Aided Design, Reflectivity, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Sky, Signal Processing, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, business, Software
Abstract

International audience; We present an image-based approach to relighting photographs of tree canopies. Our goal is to minimize capture overhead; thus the only input required is a set of photographs of the tree taken at a single time of day, while allowing relighting at any other time. We first analyze lighting in a tree canopy both theoretically and using simulations. From this analysis, we observe that tree canopy lighting is similar to volumetric illumination. We assume a single-scattering volumetric lighting model for tree canopies, and diffuse leaf reflectance; we validate our assumptions with synthetic renderings. We create a volumetric representation of the tree from 10-12 images taken at a single time of day and and use a single-scattering participating media lighting model. An analytical sun and sky illumination model provides consistent representation of lighting for the captured input and unknown target times. We relight the input image by applying a ratio of the target and input time lighting representations. We compute this representation efficiently by simultaneously coding transmittance from the sky and to the eye in spherical harmonics. We validate our method by relighting images of synthetic trees and comparing to path-traced solutions. We also present results for photographs where sparse, validating with time-lapse ground truth sequences.

Published
2011
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19. NPR Gabor Noise for Coherent Stylization

Author

Pierre Bénard, Ares Lagae, Sylvain Lefebvre, Joëlle Thollot, George Drettakis, Peter Vangorp, Acquisition, representation and transformations for image synthesis (ARTIS), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Leuven] (CS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Geometry and Lighting (ALICE), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), and Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF)

Subjects
noise, business.industry, Computer science, expressive rendering, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020207 software engineering, 02 engineering and technology, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.3: Picture/Image Generation, 3D rendering, non-photorealistic rendering, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Non-photorealistic rendering, Rendering (computer graphics), user study, Motion field, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.7: Three-Dimensional Graphics and Realism, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, temporal coherence, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Talk session: Fun In Flatland; International audience; We present a new solution for temporal coherence in non-photorealistic rendering (NPR) of animations. Given the conflicting goals of preserving the 2D aspect of the style and the 3D scene motion, any such solution is a trade-off. We observe that primitive-based methods in NPR can be seen as texture-based methods when using large numbers of primitives, leading to our key insight, namely that this process is similar to sparse convolution noise in procedural texturing. Consequently, we present a new primitive for NPR based on Gabor noise, that preserves the 2D aspect of noise, conveys the 3D motion of the scene, and is temporally continuous. We can thus use standard techniques from procedural texturing to create various styles, which we show for interactive NPR applications. We also present a user study to evaluate this and existing solutions, and to provide more insight in the trade-off implied by temporal coherence. The results of the study indicate that maintaining coherent motion is important, but also that our new solution provides a good compromise between the 2D aspect of the style and 3D motion.

Published
2010
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20. By-example Synthesis of Architectural Textures

Author

Anass Lasram, Sylvain Lefebvre, Samuel Hornus, Geometry and Lighting (ALICE), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Geometric computing (GEOMETRICA), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria), ANR: SIMILAR-CITIES,SIMILAR-CITIES, European Project: 205693,EC:FP7:ERC,ERC-2007-StG,GOODSHAPE(2008), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP), ANR-08-CORD-0021,SIMILAR-CITIES,Textures similaires par approximation procédurale pour l'exploration interactive de villes.(2008), and Lefebvre, Sylvain

Subjects
Texture atlas, image retargeting, Computer science, business.industry, architectural texture, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020207 software engineering, 02 engineering and technology, Computer Graphics and Computer-Aided Design, texture synthesis, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Rendering (computer graphics), Seam carving, Computer graphics (images), Retargeting, Shortest path problem, 0202 electrical engineering, electronic engineering, information engineering, Graph (abstract data type), 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Texture synthesis, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; Textures are often reused on different surfaces in large virtual environments. This leads to unpleasing stretch and cropping of features when textures contain architectural elements. Existing retargeting methods could adapt each texture to the size of their support surface, but this would imply storing a different image for each and every surface, saturating memory. Our new texture synthesis approach casts synthesis as a shortest path problem in a graph describing the space of images that can be synthesized. Each path in the graph describes how to form a new image by cutting strips of the source image and reassembling them in a different order. Only the paths describing the result need to be stored in memory: synthesized textures are reconstructed at rendering time. The user can control repetition of features, and may specify positional constraints. We demonstrate our approach on a variety of textures, from facades for large city rendering to structured textures commonly used in video games.

Published
2010
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21. Invisible Seams

Author

Nicolas Ray, Vincent Nivoliers, Sylvain Lefebvre, Bruno Levy, Geometry and Lighting (ALICE), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP), and Ray, Nicolas

Subjects
Texture atlas, business.industry, Computer science, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Boundary (topology), Bilinear interpolation, 020207 software engineering, 02 engineering and technology, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], 0202 electrical engineering, electronic engineering, information engineering, Bicubic interpolation, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, Texel, business, Interpolation, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; Surface materials are commonly described by attributes stored in textures (for instance, color, normal, or displacement). Interpolation during texture lookup provides a continuous value field everywhere on the surface, except at the chart boundaries where visible discontinuities appear. We propose a solution to make these seams invisible, while still outputting a standard texture atlas. Our method relies on recent advances in quad remeshing using global parameterization to produce a set of texture coordinates aligning texel grids across chart boundaries. This property makes it possible to ensure that the interpolated value fields on both sides of a chart boundary precisely match, making all seams invisible. However, this requirement on the uv coordinates needs to be complemented by a set of constraints on the colors stored in the texels. We propose an algorithm solving for all the necessary constraints between texel values, including through different magnification modes (nearest, bilinear, biquadratic and bicubic), and across facets using different texture resolutions. In the typical case of bilinear magnification and uniform resolution, none of the texels appearing on the surface are constrained. Our approach also ensures perfect continuity across several MIP-mapping levels.

Published
2010

22. A dynamic noise primitive for coherent stylization

Author

Ares Lagae, George Drettakis, Pierre Bénard, Joëlle Thollot, Sylvain Lefebvre, Peter Vangorp, Acquisition, representation and transformations for image synthesis (ARTIS), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Leuven] (CS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Geometry and Lighting (ALICE), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), K.U.Leuven CREA funding (CREA/08/017), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)

Subjects
noise, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.3: Picture/Image Generation, non-photorealistic rendering, 050105 experimental psychology, Rendering (computer graphics), 0202 electrical engineering, electronic engineering, information engineering, 0501 psychology and cognitive sciences, Computer vision, Dynamic noise, temporal coherence, ComputingMethodologies_COMPUTERGRAPHICS, expressive rendering, business.industry, 05 social sciences, 020207 software engineering, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Non-photorealistic rendering, user study, Procedural texture, Artificial intelligence, business, Algorithm
Abstract

We present a new solution for temporal coherence in non-photorealistic rendering (NPR) of animations. Given the conflicting goals of preserving the 2D aspect of the style and the 3D scene motion, any such solution is a trade-off. We observe that primitive-based methods in NPR can be seen as texture-based methods when using large numbers of primitives, leading to our key insight, namely that this process is similar to sparse convolution noise in procedural texturing. Consequently, we present a new primitive for NPR based on Gabor noise, that preserves the 2D aspect of noise, conveys the 3D motion of the scene, and is temporally continuous. We can thus use standard techniques from procedural texturing to create various styles, which we show for interactive NPR applications. We also present a user study to evaluate this and existing solutions, and to provide more insight in the trade-off implied by temporal coherence. The results of the study indicate that maintaining coherent motion is important, but also that our new solution provides a good compromise between the 2D aspect of the style and 3D motion. ispartof: Computer Graphics Forum vol:29 issue:4 pages:1497-1506 ispartof: location:Saarbrücken, Germany status: published

Published
2010
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23. Beyond Triangles : GigaVoxels Effects In Video Games

Author

Fabrice Neyret, Cyril Crassin, Miguel Sainz, Sylvain Lefebvre, Elmar Eisemann, Acquisition, representation and transformations for image synthesis (ARTIS), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), NVIDIA (NVIDIA), Télécom ParisTech, and Saarland University [Saarbrücken]

Subjects
Computer science, depth-of-field, sparse, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, GPU, 02 engineering and technology, computer.software_genre, GeneralLiterature_MISCELLANEOUS, Rendering (computer graphics), Data visualization, Voxel, Computer graphics (images), 0202 electrical engineering, electronic engineering, information engineering, Polygon mesh, Computer vision, ray-tracing, Geometric data analysis, ComputingMethodologies_COMPUTERGRAPHICS, Pixel, business.industry, 020207 software engineering, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], voxels, soft shadows, 020201 artificial intelligence & image processing, Ray tracing (graphics), Artificial intelligence, business, computer, out-of-core, ACM: K.: Computing Milieux/K.8: PERSONAL COMPUTING/K.8.0: General/K.8.0.0: Games
Abstract

Conference sessions - Talks: Rendering and Visualization; International audience; Voxel representations are commonly used for scientific data visualization, but also for many special effects involving complex or fuzzy data (e.g., clouds, smoke, foam). Since voxel rendering permits better and easier filtering than triangle-based representations it is also an efficient high-quality choice for complex meshes (with several triangles per pixel) and detailed geometric data (e.g., boats in Pirates of the Caribbean).

Published
2009
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24. Procedural noise using sparse Gabor convolution

Author

Sylvain Lefebvre, George Drettakis, Philip Dutré, Ares Lagae, Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Leuven] (CS), and Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven)

Subjects
noise, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Convolution, symbols.namesake, Image noise, 0202 electrical engineering, electronic engineering, information engineering, procedural texture, Computer vision, Value noise, ComputingMethodologies_COMPUTERGRAPHICS, Anisotropic filtering, Noise measurement, business.industry, Noise (signal processing), Bandwidth (signal processing), 020207 software engineering, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Gradient noise, Kernel (image processing), Gaussian noise, symbols, Procedural texture, rendering, 020201 artificial intelligence & image processing, Artificial intelligence, business, shading
Abstract

Noise is an essential tool for texturing and modeling. Designing interesting textures with noise calls for accurate spectral control, since noise is best described in terms of spectral content. Texturing requires that noise can be easily mapped to a surface, while high-quality rendering requires anisotropic filtering. A noise function that is procedural and fast to evaluate offers several additional advantages. Unfortunately, no existing noise combines all of these properties. In this paper we introduce a noise based on sparse convolution and the Gabor kernel that enables all of these properties. Our noise offers accurate spectral control with intuitive parameters such as orientation, principal frequency and bandwidth. Our noise supports two-dimensional and solid noise, but we also introduce setup-free surface noise. This is a method for mapping noise onto a surface, complementary to solid noise, that maintains the appearance of the noise pattern along the object and does not require a texture parameterization. Our approach requires only a few bytes of storage, does not use discretely sampled data, and is nonperiodic. It supports anisotropy and anisotropic filtering. We demonstrate our noise using an interactive tool for noise design. ispartof: ACM Transactions on Graphics vol:28 issue:3 ispartof: location:New Orleans status: published

Published
2009
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25. GigaVoxels

Author

Elmar Eisemann, Fabrice Neyret, Cyril Crassin, Sylvain Lefebvre, Acquisition, representation and transformations for image synthesis (ARTIS), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Max-Planck-Institut für Informatik (MPII), and Max-Planck-Gesellschaft

Subjects
Exploit, business.industry, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020207 software engineering, 02 engineering and technology, computer.software_genre, External Data Representation, Data structure, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], 3D rendering, Real-time rendering, Rendering (computer graphics), ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.7: Three-Dimensional Graphics and Realism, Voxel, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Polygon mesh, Computer vision, Artificial intelligence, business, computer, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; We propose a new approach to efficiently render large volumetric data sets. The system achieves interactive to real-time rendering performance for several billion voxels. Our solution is based on an adaptive data representation depending on the current view and occlusion information, coupled to an efficient ray-casting rendering algorithm. One key element of our method is to guide data production and streaming directly based on information extracted during rendering. Our data structure exploits the fact that in CG scenes, details are often concentrated on the interface between free space and clusters of density and shows that volumetric models might become a valuable alternative as a rendering primitive for real-time applications. In this spirit, we allow a quality/performance trade-off and exploit temporal coherence. We also introduce a mipmapping-like process that allows for an increased display rate and better quality through high quality filtering. To further enrich the data set, we create additional details through a variety of procedural methods. We demonstrate our approach in several scenarios, like the exploration of a 3D scan (81923 resolution), of hypertextured meshes (163843 virtual resolution), or of a fractal (theoretically infinite resolution). All examples are rendered on current generation hardware at 20-90 fps and respect the limited GPU memory budget.

Published
2009
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26. Lazy Solid Texture Synthesis

Author

Xin Tong, Sylvain Lefebvre, Yue Dong, George Drettakis, Microsoft Research Asia, Institute for Advanced Study [Tsinghua], Tsinghua University [Beijing] (THU), Rendering and virtual environments with sound (REVES), Inria Sophia Antipolis - Méditerranée (CRISAM), and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Computer science, business.industry, OpenGL, Solid texture, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, solid texture, 020207 software engineering, 02 engineering and technology, computer.software_genre, Computer Graphics and Computer-Aided Design, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Rendering (computer graphics), Voxel, synthesis texturing, volume gpu, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Shading, Artificial intelligence, business, computer, Algorithm, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; Existing solid texture synthesis algorithms generate a full volume of color content from a set of 2D example images. We introduce a new algorithm with the unique ability to restrict synthesis to a subset of the voxels, while enforcing spatial determinism. This is especially useful when texturing objects, since only a thick layer around the surface needs to be synthesized. A major difficulty lies in reducing the dependency chain of neighborhood matching, so that each voxel only depends on a small number of other voxels. Our key idea is to synthesize a volume from a set of pre-computed 3D candidates, each being a triple of interleaved 2D neighborhoods. We present an efficient algorithm to carefully select in a pre-process only those candidates forming consistent triples. This significantly reduces the search space during subsequent synthesis. The result is a new parallel, spatially deterministic solid texture synthesis algorithm which runs efficiently on the GPU. Our approach generates high resolution solid textures on surfaces within seconds. Memory usage and synthesis time only depend on the output textured surface area. The GPU implementation of our method rapidly synthesizes new textures for the surfaces appearing when interactively breaking or cutting objects.

Published
2008

27. Texture sprites

Author

Samuel Hornus, Sylvain Lefebvre, Fabrice Neyret, Virtual environments for animation and image synthesis of natural objects (EVASION), Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble (GRAVIR - IMAG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Acquisition, representation and transformations for image synthesis (ARTIS), ACM SIGGRAPH, and Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes

Subjects
Texture atlas, Texture compression, Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Data structure, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Real-time rendering, Rendering (computer graphics), Sprite (lightning), Texture filtering, Computer graphics (images), Computer vision, Artificial intelligence, business, Texture memory, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; We present a new interactive method to texture complex geometries at very high resolution, while using little memory and without the need for a global planar parameterization. We rely on small texture elements, the texture sprites, locally splatted onto the surface to define a composite texture. The sprites can be arbitrarily blended to create complex surface appearances. Their attributes (position, size, texture id) can be dynamically updated, thus providing a convenient framework for interactive editing and animated textures. We demonstrate the flexibility of our method by creating new surface aspects difficult to achieve with other methods. Each sprite is described by a small set of attributes which is stored in a hierarchical structure surrounding the object's surface. The patterns supported by the sprites are stored only once. The whole data structure is compactly encoded into GPU memory. At run time, it is accessed by a fragment program which computes the final appearance of a surface point from all the sprites covering it. The overall memory cost of the structure is very low compared to the resulting texturing resolutions. Rendering is done in real-time. The resulting texture is linearly interpolated and altered.

Published
2005
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28. Pattern Based Procedural Textures

Author

Sylvain Lefebvre, Fabrice Neyret, Virtual environments for animation and image synthesis of natural objects (EVASION), Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble (GRAVIR - IMAG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), ACM, and Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes

Subjects
proceduralism, graphics hardware, Texture atlas, Indirection, business.industry, Computer science, Graphics hardware, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020207 software engineering, 02 engineering and technology, landscape, textures, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Texture filtering, Aperiodic tiling, 0202 electrical engineering, electronic engineering, information engineering, Procedural texture, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, Graphics, business, Programmer, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

International audience; Numerous real-time applications such computer games or flight simulators require non-repetitive high-resolution texturing on large landscapes. We propose an algorithm which procedurally determines the texture value at any surface location by aperiodically combining provided patterns according to user-defined controls such as a probability distribution (possibly non stationary). Our algorithm can be implemented on programmable hardware by taking advantage of the texture indirection ability of recent graphics boards. We use explicit and virtual indirection tables to determine the pattern to apply at each pixel as well as its attributes (displacement, scaling, time...). This provides the programmer with a very high resolution virtual texture with nice properties: Low memory consumption, no periodicity, control of the statistics, numerous control parameters (which can be edited on the fly)... Our representation consists of building blocks that we combine in order to illustrate various convenient texture modalities such as aperiodic tiling, sparse convolution, domain transitions and animated textures.

Published
2003
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