Search

Your search keyword '"Favreau, Jean-Marie"' showing total 24 results
Start Over Author "Favreau, Jean-Marie" Publication Year Range Last 10 years
24 results on '"Favreau, Jean-Marie"'

2. The Calissons Puzzle

Author

Favreau, Jean-Marie, Gerard, Yan, Lafourcade, Pascal, and Robert, Léo

Subjects
Computer Science - Computational Geometry, 05B45 52C20
Abstract

In 2022, Olivier Longuet, a French mathematics teacher, created a game called the \textit{calissons puzzle}. Given a triangular grid in a hexagon and some given edges of the grid, the problem is to find a calisson tiling such that no input edge is overlapped and calissons adjacent to an input edge have different orientations. We extend the puzzle to regions $R$ that are not necessarily hexagonal. The first interesting property of this puzzle is that, unlike the usual calisson or domino problems, it is solved neither by a maximal matching algorithm, nor by Thurston's algorithm. This raises the question of its complexity. We prove that if the region $R$ is finite and simply connected, then the puzzle can be solved by an algorithm that we call the \textit{advancing surface algorithm} and whose complexity is $O(|\partial R|^3)$ where $\partial R|$ is the size of the boundary of the region $R$. In the case where the region is the entire infinite triangular grid, we prove that the existence of a solution can be solved with an algorithm of complexity $O(|X|^3)$ where $X$ is the set of input edges. To prove these theorems, we revisit William Thurston's results on the calisson tilability of a region $R$. The solutions involve equivalence between calisson tilings, stepped surfaces and certain DAG cuts that avoid passing through a set of edges that we call \textit{unbreakable}. It allows us to generalize Thurston's theorem characterizing tilable regions by rewriting it in terms of descending paths or absorbing cycles. Thurston's algorithm appears as a distance calculation algorithm following Dijkstra's paradigm. The introduction of a set $X$ of interior edges introduces negative weights that force a Bellman-Ford strategy to be preferred. These results extend Thurston's legacy by using computer science structures and algorithms., Comment: 26 pages, 20 figures

Published
2023

3. Wearable IoT Sensor Combining Deep Learning for Enhanced Human Activity Recognition in Indoor and Outdoor Settings

Author

Mhalla, Ala, Favreau, Jean-Marie, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Habachi, Oussama, editor, Chalhoub, Gerard, editor, Elbiaze, Halima, editor, and Sabir, Essaid, editor

Published
2024
Full Text
View/download PDF

5. 3D Geometric salient patterns analysis on 3D meshes

Author

Othmani, Alice, Torkhani, Fakhri, and Favreau, Jean-Marie

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics
Abstract

Pattern analysis is a wide domain that has wide applicability in many fields. In fact, texture analysis is one of those fields, since the texture is defined as a set of repetitive or quasi-repetitive patterns. Despite its importance in analyzing 3D meshes, geometric texture analysis is less studied by geometry processing community. This paper presents a new efficient approach for geometric texture analysis on 3D triangular meshes. The proposed method is a scale-aware approach that takes as input a 3D mesh and a user-scale. It provides, as a result, a similarity-based clustering of texels in meaningful classes. Experimental results of the proposed algorithm are presented for both real-world and synthetic meshes within various textures. Furthermore, the efficiency of the proposed approach was experimentally demonstrated under mesh simplification and noise addition on the mesh surface. In this paper, we present a practical application for semantic annotation of 3D geometric salient texels.

Published
2019

8. What are intersections for pedestrian users?

Author

Favreau, Jean-Marie, Kalsron, Jérémy, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), ANR ACTIVmap (ANR-19-CE19-0005), and ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019)

Subjects
intersections, graph segmentation, General Earth and Planetary Sciences, OpenStreetMap, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], pedestrian users, General Environmental Science
Abstract

The increase of accessibility and pedestrian data in geographic databases such as OpenStreetMap brings with it the possibility to find a number of applications for pedestrian users.The way in which different urban spaces are crossed obviously depends on their nature. In particular, crossing an intersection is not the same as walking along a street. Intersections are particularly complex areas, where crossing is almost mandatory, often with several possible routes.Although there are various works in the literature that are interested in locating these intersections in a road network, to our knowledge there is no work that deals with the precise segmentation of intersections at the scale of pedestrian use.In this article, we propose an approach that allows us to segment the OpenStreetMap street network at the pedestrian level, by precisely identifying the boundaries between intersections and other spaces.By combining the geometry, topology and semantics of the urban automobile network of OpenStreetMap, we propose an algorithm for locating elementary intersections, and then successively assembling them in a multi-scale approach, in order to obtain the intersections as they are considered by pedestrians during their movements. In particular, our approach relies on the elements that constitute the boundaries of these intersections, such as pedestrian crossings and traffic lights.After presenting an implementation of this approach, we offer a number of results that illustrate the robustness of the proposed approach.

Published
2022
Full Text
View/download PDF

9. A Web GIS to Generate Audio-Tactile Maps for Visually Impaired People

Author

Touya, Guillaume, Braikeh, Samuel, Campbell, Ridley, Favreau, Jean-Marie, Kalsron, Jérémy, Laboratoire sciences et technologies de l'information géographique (LaSTIG), Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Georg Gartner, Andrea Binn, Olesia Ignateva, and ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019)

Subjects
tactile map, visual impairment, web GIS, [INFO]Computer Science [cs], General Medicine, map generalisation
Published
2022
Full Text
View/download PDF

11. CrossroadsDescriber – Automatic Textual Description of OpenStreetMap Intersections

Author

Kalsron, Jérémy, Favreau, Jean-Marie, Touya, Guillaume, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Laboratoire sciences et technologies de l'information géographique (LaSTIG), Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel, Centre de recherche nantais Architectures Urbanités (CRENAU ), Ambiances, Architectures, Urbanités (AAU), Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Université Grenoble Alpes (UGA)-Université Grenoble Alpes (UGA)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-NANTES UNIVERSITÉ - École nationale supérieure d'architecture de Nantes (Nantes Univ - ENSA Nantes), Nantes Université (Nantes Univ)-Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Nantes Université (Nantes Univ), and ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019)

Subjects
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], General Earth and Planetary Sciences, General Environmental Science
Abstract

Crossing an intersection is a challenge for visually impaired people. While tactile maps can be a medium for appropriating this complex space, they benefit from being complemented by audio information. In this paper we propose a data model to describe an intersection, the paths that allow to cross it, and their accessibility attributes. We also present methods to generate this model automatically from OpenStreetMap, by inferring missing data through graph analysis techniques. Finally, we present an implementation, the evaluation of which confirms the ability of the model to generate a compliant description for intersections with enough data.

Published
2022
Full Text
View/download PDF

13. Schematizing Crossroads from Abstract Textual Descriptions

Author

Favreau, Jean-Marie, Touya, Guillaume, Kalsron, Jérémy, Touya, Guillaume, Assistance à la Conception de carTes pour défIcients Visuels - - ACTIVmap2019 - ANR-19-CE19-0005 - AAPG2019 - VALID, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Laboratoire sciences et technologies de l'information géographique (LaSTIG), Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel, Centre de recherche nantais Architectures Urbanités (CRENAU ), Ambiances, Architectures, Urbanités (AAU), Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Université Grenoble Alpes (UGA)-Université Grenoble Alpes (UGA)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-NANTES UNIVERSITÉ - École nationale supérieure d'architecture de Nantes (Nantes Univ - ENSA Nantes), Nantes Université (Nantes Univ)-Ministère de la Culture et de la Communication (MCC)-Centre National de la Recherche Scientifique (CNRS)-École nationale supérieure d'architecture de Grenoble (ENSAG ), Nantes Université (Nantes Univ), University of Bonn, Germany, and ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019)

Subjects
Computational cartography, Cartography, Cartographie -- informatique, [INFO]Computer Science [cs], [INFO] Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2022

14. Fine Detection of Human Motion During Activities of Daily Living as a Clinical Indicator for the Detection and Early Treatment of Chronic Diseases: The E-Mob Project

Author

Thivel, David, primary, Corteval, Alice, additional, Favreau, Jean-Marie, additional, Bergeret, Emmanuel, additional, Samalin, Ludovic, additional, Costes, Frédéric, additional, Toumani, Farouk, additional, Dualé, Christian, additional, Pereira, Bruno, additional, Eschalier, Alain, additional, Fearnbach, Nicole, additional, Duclos, Martine, additional, and Tournadre, Anne, additional

Published
2022
Full Text
View/download PDF

15. 3D Geometric salient patterns analysis on 3D meshes

Author

Othmani, Alice, Torkhani, Fakhri, Favreau, Jean-Marie, Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), and Favreau, Jean-Marie

Subjects
FOS: Computer and information sciences, Computer Science - Graphics, [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], Graphics (cs.GR), ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Pattern analysis is a wide domain that has wide applicability in many fields. In fact, texture analysis is one of those fields, since the texture is defined as a set of repetitive or quasi-repetitive patterns. Despite its importance in analyzing 3D meshes, geometric texture analysis is less studied by geometry processing community. This paper presents a new efficient approach for geometric texture analysis on 3D triangular meshes. The proposed method is a scale-aware approach that takes as input a 3D mesh and a user-scale. It provides, as a result, a similarity-based clustering of texels in meaningful classes. Experimental results of the proposed algorithm are presented for both real-world and synthetic meshes within various textures. Furthermore, the efficiency of the proposed approach was experimentally demonstrated under mesh simplification and noise addition on the mesh surface. In this paper, we present a practical application for semantic annotation of 3D geometric salient texels.

Published
2020

16. Le carrefour dont vous êtes le héros

Author

Kalsron, Jérémy, Favreau, Jean-Marie, Touya, Guillaume, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), ANR-19-CE19-0005,ACTIVmap,Assistance à la Conception de carTes pour défIcients Visuels(2019), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Kalsron, Jérémy, and Assistance à la Conception de carTes pour défIcients Visuels - - ACTIVmap2019 - ANR-19-CE19-0005 - AAPG2019 - VALID

Subjects
[SHS.GEO] Humanities and Social Sciences/Geography, [SHS.GEO]Humanities and Social Sciences/Geography, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

17. Fine Detection of Human Motion During Activities of Daily Living as a Clinical Indicator for the Detection and Early Treatment of Chronic Diseases: The E-Mob Project (Preprint)

Author

Thivel, David, primary, Corteval, Alice, additional, Favreau, Jean-Marie, additional, Bergeret, Emmanuel, additional, Samalin, Ludovic, additional, Costes, Frédéric, additional, Toumani, Farouk, additional, Dualé, Christian, additional, Pereira, Bruno, additional, Eschalier, Alain, additional, Fearnbach, Nicole, additional, Duclos, Martine, additional, and Tournadre, Anne, additional

Published
2021
Full Text
View/download PDF

20. Technical Report : 3D mesh Segmentation Application to glasses

Author

Bernay-Angeletti, Coralie, Favreau, Jean-Marie, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), FEDER 2014-2020 Auvergne-Rhône-Alpes, LIMOS (UMR CNRS 6158), université Clermont Auvergne, France, and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]
Abstract

Object segmentation in meaningfull parts is an important research topic as these have become a part of many mesh and object manipulation algorithms in computer graphics, geometric modelling and computer aided design. In particular, tasks that were before realized by experts are more and more assumed by people without particular formation in geometric or computer graphic problems. So there is a need to have some ergonomic tools that have expert know-how while user keep control on specific constraints to its particular application. Here, we present how for segmentation purpose we model expert know-how and two algorithms that can be used to make segmentation task. One is generic and the other is specialized for glasses segmentations.

Published
2017

22. Automatic derivation of on-demand tactile maps for visually impaired people: first experiments and research agenda

Author

Touya, Guillaume, Christophe, Sidonie, Favreau, Jean-Marie, and Ben Rhaiem, Amine

Abstract

ABSTRACTTactile maps are essential tools for visually impaired people to comprehend space and to support the simple pedestrian trips made difficult by their disability. Tactile maps are created manually and printed by specialists, and it takes a large amount of time to create a new one, which prevents using them on demand for everyday use. As a consequence, researchers and cartographers try to automate this creation process, but the existing automated derivation processes do not include generalization or advanced stylization steps, which limits their effectiveness. This paper reports first experiments to include such complex automated cartography processes to provide on-demand tactile maps for visually impaired people. These first experiments were more intended to raise real research issues than solve them, and the paper discusses these issues in a research agenda to achieve automatically derived tactile maps.

Published
2019
Full Text
View/download PDF

24. Multi-layer Ontologies for Integrated 3D Shape Segmentation and Annotation

Author

Fakhri Torkhani, Thomas Dietenbeck, Marco Attene, Jean-Marie Favreau, Ahlem Othmani, 2 - Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), IMATI, Istituto di Matematica Applicata e Tecnologie Informatiche ( IMATI-CNR ), Consiglio Nazionale delle Ricerche [Roma] ( CNR ) -Consiglio Nazionale delle Ricerche [Roma] ( CNR ), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes ( LIMOS ), Sigma CLERMONT ( Sigma CLERMONT ) -Université Clermont Auvergne ( UCA ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Istituto di Matematica Applicata e Tecnologie Informatiche (IMATI-CNR), Consiglio Nazionale delle Ricerche [Roma] (CNR)-Consiglio Nazionale delle Ricerche [Roma] (CNR), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Favreau, Jean-Marie, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)-National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer science, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, Image processing, 02 engineering and technology, Geometry processing, Ontology (information science), computer.software_genre, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Expert system, Annotation, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG], N/A, 0202 electrical engineering, electronic engineering, information engineering, [ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG], Preprocessor, Domain knowledge, 020201 artificial intelligence & image processing, Segmentation, Data mining, computer
Abstract

Mesh segmentation and semantic annotation are used as preprocessing steps formany applications, including shape retrieval, mesh abstraction, and adaptive simplification. In current practice, these two steps are done sequentially: a purely geometrical analysis is employed to extract the relevant parts, and then these parts are annotated. We introduce an original framework where annotation and segmentation are performed simultaneously, so that each of the two steps can take advantage of the other. Inspired by existing methods used in image processing, we employ an expert's knowledge of the context to drive the process while minimizing the use of geometric analysis. For each specific context a multi-layer ontology can be designed on top of a basic knowledge layer which conceptualizes 3D object features from the point of view of their geometry, topology, and possible attributes. Each feature is associated with an elementary algorithm for its detection. An expert can define the upper layers of the ontology to conceptualize a specific domain without the need to reconsider the elementary algorithms. This approach has a twofold advantage: on one hand it allows Mesh segmentation and semantic annotation are used as preprocessing steps formany applications, including shape retrieval, mesh abstraction, and adaptive simplification. In current practice, these two steps are done sequentially: a purely geometrical analysis is employed to extract the relevant parts, and then these parts are annotated. We introduce an original framework where annotation and segmentation are performed simultaneously, so that each of the two steps can take advantage of the other. Inspired by existing methods used in image processing, we employ an expert's knowledge of the context to drive the process while minimizing the use of geometric analysis. For each specific context a multi-layer ontology can be designed on top of a basic knowledge layer which conceptualizes 3D object features from the point of view of their geometry, topology, and possible attributes. Each feature is associated with an elementary algorithm for its detection. An expert can define the upper layers of the ontology to conceptualize a specific domain without the need to reconsider the elementary algorithms. This approach has a twofold advantage: on one hand it allows Mesh segmentation and semantic annotation are used as preprocessing steps formany applications, including shape retrieval, mesh abstraction, and adaptive simplification. In current practice, these two steps are done sequentially: a purely geometrical analysis is employed to extract the relevant parts, and then these parts are annotated. We introduce an original framework where annotation and segmentation are performed simultaneously, so that each of the two steps can take advantage of the other. Inspired by existing methods used in image processing, we employ an expert's knowledge of the context to drive the process while minimizing the use of geometric analysis. For each specific context a multi-layer ontology can be designed on top of a basic knowledge layer which conceptualizes 3D object features from the point of view of their geometry, topology, and possible attributes. Each feature is associated with an elementary algorithm for its detection. An expert can define the upper layers of the ontology to conceptualize a specific domain without the need to reconsider the elementary algorithms. This approach has a twofold advantage: on one hand it allows to leverage domain knowledge from experts even if they have limited or no skills in geometry processing and computer programming; on the other hand, it provides a solid ground to be easily extended in different contexts with a limited effort.

Published
2016
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results