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We propose an efficient method to model paper tearing in the context of interactive modeling. The method uses geometrical information to automatically detect potential starting points of tears. We further introduce a new hybrid geometrical and physical-based method to compute the trajectory of tears while procedurally synthesizing high resolution details of the tearing path using a texture based approach. The results obtained are compared with real paper and with previous studies on the expected geometric paths of paper that tears. [ABSTRACT FROM AUTHOR]

Paper pop-ups are interesting three-dimensional books that fascinate people of all ages. The design and construction of these pop-up books however are done manually and require a lot of time and effort. This has led to computer-assisted or automated tools for designing paper pop-ups. This paper proposes an approach for automatically converting a 3D model into a multi-style paper pop-up. Previous automated approaches have only focused on single-style pop-ups, where each is made of a single type of pop-up mechanisms. In our work, we combine multiple styles in a pop-up, which is more representative of actual artist's creations. Our method abstracts a 3D model using suitable primitive shapes that both facilitate the formation of the considered pop-up mechanisms and closely approximate the input model. Each shape is then abstracted using a set of 2D patches that combine to form a valid pop-up. We define geometric conditions that ensure the validity of the combined pop-up structures. In addition, our method also employs an image-based approach for producing the patches to preserve the textures, finer details and important contours of the input model. Finally, our system produces a printable design layout and decides an assembly order for the construction instructions. The feasibility of our results is verified by constructing the actual paper pop-ups from the designs generated by our system. [ABSTRACT FROM AUTHOR]

Background: Computerized methods to analyze pain drawings (PDs) have been developed and may aid to measure the pain area more precisely. Objective: The aim of this study was to verify whether examiners can reproduce the patient's PDs with acceptable reliability. Methods: This was an intra‐rater and inter‐rater reliability study. The protocol consisted of 4 steps: (1) scanning of paper PDs; (2) sharing the digitalized PD images between examiners; (3) reproducing the PD images in the sketching application; and (4) calculating the pain area in pixels and percentages. We calculated intraclass correlation coefficients (ICCs; 2,1), the standard error of the measurement (SEM), and the smallest detectable difference (SDD). Results: Reliability was tested using 31 PDs from 17 patients in our database (11 female [64.7%], mean age: 53.23 ± 11.57 years). Intra‐rater reliability varied from ICC (2,1) = 0.991 (95% confidence interval [CI] = 0.982 to 0.996; SEM = 3,432.45; SDD = 162.39 pixels; P < 0.001) to ICC (2,1) = 0.992 (95% CI = 0.978 to 0.997; SEM = 3,412.96; SDD = 161.93 pixels; P < 0.001). Inter‐rater reliability for the measurement between all examiners was considered excellent (ICC [2,1] = 0.976; 95% CI = 0.956 to 0.987; SEM =8,580.75; SDD = 256.76 pixels; P < 0.001), being higher between Examiners A and C (ICC [2,1] = 0.970; 95% CI = 0.936 to 0.986; SEM = 6,453.34; SDD = 222.67 pixels; P < 0.001). Conclusion: Our results show that intra‐ and inter‐rater reliabilities were excellent when an examiner reproduced the paper PDs into digitalized PDs. This process gives clinicians and researchers the opportunity to analyze pain extent more precisely using a computerized method. [ABSTRACT FROM AUTHOR]

We present a novel appearance model for paper. Based on our appearance measurements for matte and glossy paper, we find that paper exhibits a combination of subsurface scattering, specular reflection, retroreflection, and surface sheen. Classic microfacet and simple diffuse reflection models cannot simulate the double-sided appearance of a thin layer. Our novel BSDF model matches our measurements for paper and accounts for both reflection and transmission properties. At the core of the BSDF model is a method for converting a multi-layer subsurface scattering model (BSSRDF) into a BSDF, which allows us to retain physically-based absorption and scattering parameters obtained from the measurements. We also introduce a method for computing the amount of light available for subsurface scattering due to transmission through a rough dielectric surface. Our final model accounts for multiple scattering, single scattering, and surface reflection and is capable of rendering paper with varying levels of roughness and glossiness on both sides. [ABSTRACT FROM AUTHOR]

Keeping up with rapidly growing research fields, especially when there are multiple interdisciplinary sources, requires substantial effort for researchers, program managers, or venture capital investors. Current theories and tools are directed at finding a paper or website, not gaining an understanding of the key papers, authors, controversies, and hypotheses. This report presents an effort to integrate statistics, text analytics, and visualization in a multiple coordinated window environment that supports exploration. Our prototype system, Action Science Explorer ( ASE), provides an environment for demonstrating principles of coordination and conducting iterative usability tests of them with interested and knowledgeable users. We developed an understanding of the value of reference management, statistics, citation text extraction, natural language summarization for single and multiple documents, filters to interactively select key papers, and network visualization to see citation patterns and identify clusters. A three-phase usability study guided our revisions to ASE and led us to improve the testing methods. [ABSTRACT FROM AUTHOR]

Reviewing literatures for a certain research field is always important for academics. One could use Google-like information seeking tools, but oftentimes he/she would end up obtaining too many possibly related papers, as well as the papers in the associated citation network. During such a process, a user may easily get lost after following a few links for searching or cross-referencing. It is also difficult for the user to identify relevant/important papers from the resulting huge collection of papers. Our work, called PaperVis, endeavors to provide a user-friendly interface to help users quickly grasp the intrinsic complex citation-reference structures among a specific group of papers. We modify the existing Radial Space Filling (RSF) and Bullseye View techniques to arrange involved papers as a node-link graph that better depicts the relationships among them while saving the screen space at the same time. PaperVis applies visual cues to present node attributes and their transitions among interactions, and it categorizes papers into semantically meaningful hierarchies to facilitate ensuing literature exploration. We conduct experiments on the InfoVis 2004 Contest Dataset to demonstrate the effectiveness of PaperVis. [ABSTRACT FROM AUTHOR]

Current desktop technology is largely mouse-driven, but many analysts predict that in less than five years we will have a professional workforce that have only experienced learning in a touchscreen environment. Midland Valley have developed a digital mapping tool for smartphones called FieldMove Clino, which has been downloaded more than 20 000 times over the past year. The free version offers an effective way of introducing students to digital field mapping. However, many geoscience departments and teachers of field mapping have yet to make the switch from traditional paper-based methods to digital technology. This article aims to answer some of the frequently asked questions about digital field mapping and outlines some of the advantages for improving field skills and geological thinking in students. [ABSTRACT FROM AUTHOR]

New and rapidly‐evolving classes of display devices bridge the gap between us and the immersive experiences of the future. The most intimate of these displays are the Virtual‐ and Augmented‐Reality (VR and AR) ones, because they are capable of presenting synthetic environments that rival those in the real world. This ecosystem of personal and highly‐immersive displays offers new challenges for research in computer graphics, display technologies, and human visual perception. While the extensive advancements in the areas of display and computer graphics technologies traditionally end at the on‐screen "image," there are several untapped opportunities for advances that exploit the interplay between the display characteristics and how our visual system perceives them. In this article, we review recent progress in understanding and modeling the perception of immersive displays, as well as perceptually optimizing display technologies for immersive experiences. We present this review in the form of a taxonomy that maps the various properties of modern displays with the perceptual phenomenon that most closely interacts with them. From this taxonomy, we deduce several unsolved challenges in understanding human perception of displays, as well as perceptually‐optimal characteristics of future displays. [ABSTRACT FROM AUTHOR]

We present a novel and effective method for modeling a developable surface to simulate paper bending in interactive and animation applications. The method exploits the representation of a developable surface as the envelope of rectifying planes of a curve in 3D, which is therefore necessarily a geodesic on the surface. We manipulate the geodesic to provide intuitive shape control for modeling paper bending. Our method ensures a natural continuous isometric deformation from a piece of bent paper to its flat state without any stretching. Test examples show that the new scheme is fast, accurate, and easy to use, thus providing an effective approach to interactive paper bending. We also show how to handle non-convex piecewise smooth developable surfaces. [ABSTRACT FROM AUTHOR]

However, as host-switch graph cannot represent such systems, the authors investigate interconnection networks with multi-port hosts by introducing a multi-ported host-switch graph. The past years have seen a flurry of activity in the area of distributed computing and its related fields. The accepted papers for this special issue address the following aspects in computing and networking: Parallel and distributed computing Security and privacy Interconnection networks Artificial intelligence Self-stabilizing algorithms Parallel and distributed computing The first contribution, entitled "Efficient Parallel Implementations to Compute the Diameter of a Graph" by Takafuji et al., presents an efficient implementations of the Blocked Floyd-Warshall algorithm, which uses no barrier synchronization and invokes only one kernel call by using Single Kernel Soft Synchronization (SKSS) techniques. [Extracted from the article]

This paper presents models for graphite pencil, drawing paper, blenders, and kneaded eraser that produce realistic looking pencil marks, textures, and tones. Our models are based on an observation of how lead pencils interact with drawing paper, and on the absorptive and dispersive properties of blenders and erasers interacting with lead material deposited over drawing paper. The models consider parameters such as the particle composition of the lead, the texture of the paper, the position and shape of the pencil materials, and the pressure applied to them. We demonstrate the capabilities of our approach with a variety of images and compare them to digitized pencil drawings. We also present image-based rendering results implementing traditional graphite pencil tone rendering methods. [ABSTRACT FROM AUTHOR]

Constructing a 3D papercraft model from its unfolding has been fun for both children and adults since we can reproduce virtual 3D models in the real world. However, facilitating the papercraft construction process is still a challenging problem, especially when the shape of the input model is complex in the sense that it has large variation in its surface curvature. This paper presents a new heuristic approach to unfolding 3D triangular meshes without any shape distortions, so that we can construct the 3D papercraft models through simple atomic operations for gluing boundary edges around the 2D unfoldings. Our approach is inspired by the concept of topological surgery, where the appearance of boundary edges of the unfolded closed surface can be encoded using a symbolic representation. To fully simplify the papercraft construction process, we developed a genetic-based algorithm for unfolding the 3D mesh into a single connected patch in general, while optimizing the usage of the paper sheet and balance in the shape of that patch. Several examples together with user studies are included to demonstrate that the proposed approach works well for a broad range of 3D triangular meshes. [ABSTRACT FROM AUTHOR]

This awarded paper is: Simulation of collective pursuit-evasion behavior with runtime situational awareness by Zhenjing Yu, Tan Junyin, and Sheng Li, from Peking University, China. All papers have been reviewed by two or three reviewers of the CGI 2022 Program Committee, revised according to the reviewers' comments, and checked and reviewed again by the CAVW Editorial Board. This special issue is dedicated to the best papers of the second Call of the CGI 2022 conference. [Extracted from the article]

Papercraft models can serve as inexpensive prototypes in shape design applications. However, in making the models some geometric detail is necessarily lost, and artificial creases may be visible, thereby limiting the utility of these models. To compensate for these practical limitations, we introduce the use of printed patterns on papercraft models to enhance the perception of the shape they are intended to represent. We propose pattern generation schemes that modulate the sizes, directions, and densities of glyphs of patterns based on geometric attributes. We present a psychophysical experiment designed to explore the effect that printed patterns have on the perception of the papercraft model shapes. We find that models with printed patterns are perceived to represent the intended shape more accurately, and, further, that the type of printed pattern has an impact on the perceived shape. [ABSTRACT FROM AUTHOR]

We present a physically inspired model of wax crayons, which synthesizes drawings from collections of user-specified strokes. Paper is represented by a height-field texture, and a crayon is modeled with a 2D mask that evolves as it interacts with the paper. The amount of wax deposition is computed based on the crayon contact profile, contact force and friction. Previously deposited wax is smeared by crayon action, based on wax softness and contact information. Deposited wax can also be carved from the paper by the crayon and redeposited at another location. The distributed wax is rendered using a simplified Kubelka–Monk model, which approximates light transmission and scattering effects. [ABSTRACT FROM AUTHOR]

The article presents information on selected papers from the 18th Brazilian Symposium on Computer Graphics and Image Processing Rio Grande do Norte, Brazil. The paper "A Randomized Approach for Patch-based Texture Synthesis Using Wavelets" by Leandro Tonietto, Marcelo Walter and Claudio R. Jung, discusses a wavelet-based approach for selecting blocks in patch-based texture synthesis. The second paper was "GEncode: Geometry-driven Compression for General Meshes" by Thomas Lewiner and colleagues.

Information on the journal "Computer Graphics Forum" is presented, including its editorial staff, subscription rates and copyright.

In recent years, most video segmentation methods use deep CNN to process the input image, but they did not fully mine the rich intermediate predictions in spatio‐temporal space. And, the segmentation challenges such as occlusion, severe deformation and illumination have not been well solved so far. To alleviate these problems, this paper focuses on constructing multi module network structures that represent multi semantics and proposes a video object segmentation network via coupled‐stream architecture with feature memory mechanism. This network first extracts high‐level semantic features, edge features, long‐term and short‐term stable depth features of the target, and then decode them into the segmentation mask of target. In addition, negative skeleton inhibition and frame interpolation are used to prevent the interference of similar objects and motion blur, respectively. The method has a low GPU memory usage, regardless of the number of object in video. And performs 86.5%and 62.4% in J&F measure on DAVIS 2016 and DAVIS 2017 validation set, without fine‐tuning and online training. [ABSTRACT FROM AUTHOR]

Three‐dimensional reconstruction of medical tomographic images is a technological way to provides a 3D model of biological tissue. As it not only provides a 3D model, but also shows the spatial location of this model, it received widespread attention. By human‐computer interaction, doctors can easily conduct disease analysis and surgical planning. This paper introduces a novel three‐dimensional reconstruction technology of magnetic resonance images, which deals with the brightness, contrast adjustment, and three‐dimensional reconstruction of Dicom images. This paper uses the Visualization Toolkit VTK to implement Dicom 3D image reconstruction. VTK has a large number of callable functions built in and encapsulates some common visualization algorithms. When visualizing medical data, VTK can directly call the related functions. VTK three‐dimensional reconstruction can help people intuitively see the contents of a 3D image. Displaying two‐ dimensional images is easy, but displaying 3D images is not. Previously, because of the limited technical means, even if the data of the 3D image is obtained, it can only be displayed as a slice of the 2D image, which is not intuitive. With the development of computer science and technology, the use of computer graphics technology to model and render 3D objects in real‐time has become the mainstream method of object display, while the past two‐dimensional display method has been gradually phased out. To describe the process of 3D modeling more accurately and intuitively, this paper focuses on a reconstruction technique, polygon drawing. Polygon drawing uses segmentation technology to perform contour recognition, extraction, and other operations on a series of two‐dimensional images, and ultimately restores the three‐dimensional model of the detected object and displays it as a surface. First, the original data is a discrete three‐dimensional spatial rule data field. The images generated by CT and MRI of tomography scanners belong to this data type, that is, the DICOM type image used in this paper. Second, the boundary between the content part and the background part in the three‐dimensional image is found in the unit of volume, and triangles are extracted to fit the boundary. Then, all the voxels are traversed to find out which triangles are finally assembled to form a triangular mesh of the surface of the real point in the image. Finally, a triangle mesh model is built to render the model, and the rendered model is put into the window to interact with users. [ABSTRACT FROM AUTHOR]

Recognizing the detailed information embedded in rasterized floorplans is at the research forefront in the community of computer graphics and vision. With the advent of deep neural networks, automatic floorplan recognition has made tremendous breakthroughs. However, co‐recognizing both the structures and semantics of floorplans through one neural network remains a significant challenge. In this paper, we introduce a novel framework Raster‐to‐Graph, which automatically achieves structural and semantic recognition of floorplans. We represent vectorized floorplans as structural graphs embedded with floorplan semantics, thus transforming the floorplan recognition task into a structural graph prediction problem. We design an autoregressive prediction framework using the neural network architecture of the visual attention Transformer, iteratively predicting the wall junctions and wall segments of floorplans in the order of graph traversal. Additionally, we propose a large‐scale floorplan dataset containing over 10,000 real‐world residential floorplans. Our autoregressive framework can automatically recognize the structures and semantics of floorplans. Extensive experiments demonstrate the effectiveness of our framework, showing significant improvements on all metrics. Qualitative and quantitative evaluations indicate that our framework outperforms existing state‐of‐the‐art methods. Code and dataset for this paper are available at: https://github.com/HSZVIS/Raster-to-Graph. [ABSTRACT FROM AUTHOR]

In the field of scientific visualization, the upscaling of time‐varying volume is meaningful. It can be used in in situ visualization to help scientists overcome the limitations of I/O speed and storage capacity when analysing and visualizing large‐scale, time‐varying simulation data. This paper proposes self‐attention residual network‐based spatial super‐resolution (SARN‐SSR), a spatial super‐resolution model based on self‐attention residual networks that can generate time‐varying data with temporal coherence. SARN‐SSR consists of two components: a generator and a discriminator. The generator takes the low‐resolution volume sequences as the input and gives the corresponding high‐resolution volume sequences as the output. The discriminator takes both synthesized and real high‐resolution volume sequence as the input and gives a matrix to predict the realness as the output. To verify the validity of SARN‐SSR, four sets of time‐varying volume datasets are applied from scientific simulation. In addition, SARN‐SSR is compared on these datasets, both qualitatively and quantitatively, with two deep learning‐based techniques and one traditional technique. The experimental results show that by using this method, the closest time‐varying data to the ground truth can be obtained. [ABSTRACT FROM AUTHOR]

Most existing multi‐view stereo (MVS) methods fail to consider global context information in the stage of feature extraction and cost aggregation. As transformers have shown remarkable performance on various vision tasks due to their ability to perceive global contextual information, this paper proposes a transformer‐based feature enhancement network (TF‐MVSNet) to facilitate feature representation learning by combining local features (both 2D and 3D) with long‐range contextual information. To reduce memory consumption of feature matching, the cross‐attention mechanism is leveraged to efficiently construct 3D cost volumes under the epipolar constraint. Additionally, a colour‐guided network is designed to refine depth maps at a coarse stage, hence reducing incorrect depth predictions at a fine stage. Extensive experiments were performed on the DTU dataset and Tanks and Temples (T&T) benchmark and results are reported. [ABSTRACT FROM AUTHOR]

The vergence- accommodation conflict is considered to be a major problem for near-distance tasks in HMD for virtual reality (VR), and various potential solutions have been proposed [1]. 9.3: Invited Paper: Influence of Binocular Field of View Deficiencies on Visual Search Task in Head-Mounted Display. International Conference on Display Technology 2020 (V olume 52, Issue S1) 66 Influence of Binocular Field of View Deficiencies on Visual Search Task in Head-Mounted Display Mei Guo, Yue Liu* School of Optics and Photonics, Beijing Institute of Technology, Beijing, China, 100081 With the gradually-increased usage of head-mounted displays (HMD), more people are now concerned about the potential adverse effects associated with prolonged viewing of near-eye stereoscopic displays. [Extracted from the article]

We propose a generic pigment model suitable for digital painting in a wide range of genres including traditional Chinese painting and water-based painting. The model embodies a simulation of the pigment-water solution and its interaction with the brush and the paper at the level of pigment particles; such a level of detail is needed for achieving highly intricate effects by the artist. The simulation covers pigment diffusion and sorption processes at the paper surface, and aspects of pigment particle deposition on the paper. We follow rules and formulations from quantitative studies of adsorption and diffusion processes in surface chemistry and the textile industry. The result is a pigment model that spans a continuum from the very wet to the very dry brush stroke effects. We also propose a new pigment mixing method based on machine learning techniques to emulate pigment mixing in real life as well as to support the creation of new artificial pigments. To experiment with the proposed model, we embedded the model in a sophisticated digital brush system. The combined system exhibits interactive speed on a modest PC platform. provides supplementary materials for this paper. [ABSTRACT FROM AUTHOR]

In this paper, a method of stroke‐based rendering is proposed for image representation and reconstruction. The proposed method involves compositing a set of ellipses that greatly vary in location, size, rotation angle, color, and opacity. This study proves that alpha compositing is differentiable if a two‐dimensional Gaussian function is used to draw a solid ellipse. The gradient method can then be employed for automatically identifying the parameters of each ellipse such that the difference between the input image and the composited image is minimized. Experimental results indicate that the proposed method can represent various types of images including portraits, landscapes, buildings, street scenes, artificial objects, medical images etc. The proposed method can particularly render the most details and significant features of an input image with fewer strokes compared to other stroke‐based rendering algorithms. This study also demonstrates that the proposed method can be applied in painting style simulation and sparse‐view computed tomography imaging. [ABSTRACT FROM AUTHOR]

This paper presents an interactive system for ink splattering, a form of abstract art that artists splat ink onto the canvas. The default input device of our system is a pressure-sensitive 2D stylus, the most common sketching tool for digital artists, and we propose two interaction mode: ink-flicking mode and ink-dripping mode, that are designed to be analogous to the artistic techniques of ink splattering in real world. The core of our ink splattering system is a novel three-stage ink splattering framework that simulates the physics-based interaction of ink with different mediums including brush heads, air and paper. We have implemented the physical engine in CUDA and the whole simulation process runs at interactive speed. [ABSTRACT FROM AUTHOR]

Researchers in non-photorealistic rendering have investigated the display of three-dimensional worlds using various display models. In particular, recent work has focused on the modeling of traditional artistic media and styles such as pen-and-ink illustration and watercolor painting. By providing 3D rendering systems that use these alternative display models users can generate traditional illustration renderings of their three-dimensional worlds. In this paper we present our graphite pencil 3D renderer. We have broken the problem of simulating pencil drawing down into four fundamental parts: (1) simulating the drawing materials (graphite pencil and drawing paper, blenders and kneaded eraser), (2) modeling the drawing primitives (individual pencil strokes and mark-making to create tones and textures), (3) simulating the basic rendering techniques used by artists and illustrators familiar with pencil rendering, and (4) modeling the control of the drawing composition. Each part builds upon the others and is essential to developing the framework for higher-level rendering methods and tools. In this paper we present parts 2, 3, and 4 of our research. We present non-photorealistic graphite pencil rendering methods for outlining and shading. We also present the control of drawing steps from preparatory sketches to finished rendering results. We demonstrate the capabilities of our approach with a variety of images generated from 3D models. [ABSTRACT FROM AUTHOR]

Information on Eurographics conference held from Monday 4th to Friday 8th September, 2006 at Vienna, Austria is presented. Several social events, a chamber orchestra, live classical music with a touch of Viennese culture marked the opening session. Other events included animation shows, presentation of papers by the members of International Programme Committee, industry talks and games competition. Photographs of the event, sponsored by Nokia, ATI, SONY and others is also presented.

An invitation for the submission of papers for the 2009 Symposium on Computational Aesthetics in Victoria, British Columbia is presented.

In approximation theory, classical discrete operators, like generalized sampling, Szász‐Mirak'jan, Baskakov, and Bernstein operators, have been extensively studied for scalar functions. In this paper, we look at the approximation of curves by a class of discrete operators, and we exhibit graphical examples concerning several cases. The topic has useful implications about the computer graphics and the image processing: We discuss applications on the approximation and the reconstruction of curves in images. [ABSTRACT FROM AUTHOR]

Summary: Cracks can develop in high‐rise buildings because of long‐term environmental changes and extreme loading events such as strong winds or earthquakes. Although deep learning‐based identification methods can efficiently identify cracks, the accuracy of crack identification in high‐rise buildings needs to be improved due to the lack of crack datasets specifically related to high‐rise structures. Moreover, the number of available images of cracks in high‐rise is limited. To this end, this paper establishes an intelligent crack identification method based on a photorealistic synthetic modeling technique. First, a computer graphics (CG) model of a high‐rise building with assumed damage is constructed. Subsequently, the CG model is utilized to generate a dataset that includes photorealistic images of the high‐rise building as well as corresponding labels for various components and types of damage. The generated dataset is then used to train a DeepLabv3 + neural network for structural component and damage identification, followed by validation by employing images of both synthetic and full‐scale high‐rise buildings. The trained network can accurately identify different components in images of the full‐scale, high‐rise building and identify cracks that are intentionally synthesized in those images. The results show that the synthetic dataset generated by the CG model not only allows for fast and efficient labeling for the purpose of neural network training but also outperforms methods that do not consider any application‐specific context in crack identification. [ABSTRACT FROM AUTHOR]

Knitted fabric simulation seeks to create lifelike virtual representations of various knitted items like sweaters and socks using mathematical models and advanced simulation techniques. Significant advancements have been achieved in this area. Visual simulations of these fabrics now boast enhanced details, textures, and colors, closely resembling real‐world counterparts. Additionally, physical simulations have improved the movement and deformation aspects of virtual knitted fabrics, enhancing their realism. However, challenges remain. One major concern is the computational demands of these simulations, which can hinder real‐time interactions. Another issue is refining the accuracy of material models, especially when simulating diverse fibers and textures. This paper aims to review the current state of knitted fabric simulation and speculate on its future directions. [ABSTRACT FROM AUTHOR]

An editorial is presented which discusses about the reports from Thomson Reuters, making impact on computer graphics and its subfields and partnership with two major events in computer graphics that includes Symposium on Computer Animation and Conference on High-Performance Graphics.

The estimation of differential quantities on oriented point cloud is a classical step for many geometry processing tasks in computer graphics and vision. Even if many solutions exist to estimate such quantities, they usually fail at satisfying both a stable estimation with theoretical guarantee, and the efficiency of the associated algorithm. Relying on the notion of corrected curvature measures [LRT22, LRTC20] designed for surfaces, the method introduced in this paper meets both requirements. Given a point of interest and a few nearest neighbours, our method estimates the whole curvature tensor information by generating random triangles within these neighbours and normalising the corrected curvature measures by the corrected area measure. We provide a stability theorem showing that our pointwise curvatures are accurate and convergent, provided the noise in position and normal information has a variance smaller than the radius of neighbourhood. Experiments and comparisons with the state‐of‐the‐art confirm that our approach is more accurate and much faster than alternatives. The method is fully parallelizable, requires only one nearest neighbour request per point of computation, and is trivial to implement. [ABSTRACT FROM AUTHOR]

Realistic cloth rendering is a longstanding challenge in computer graphics due to the intricate geometry and hierarchical structure of cloth: Fibers form plies which in turn are combined into yarns which then are woven or knitted into fabrics. Previous fiber‐based models have achieved high‐quality close‐up rendering, but they suffer from high computational cost, which limits their practicality. In this paper, we propose a novel hierarchical model that analytically aggregates light simulation on the fiber level by building on dual‐scattering theory. Based on this, we can perform an efficient simulation of ply and yarn shading. Compared to previous methods, our approach is faster and uses less memory while preserving a similar accuracy. We demonstrate both through comparison with existing fiber‐based shading models. Our yarn shading model can be applied to curves or surfaces, making it highly versatile for cloth shading. This duality paired with its simplicity and flexibility makes the model particularly useful for film and games production. [ABSTRACT FROM AUTHOR]

The G8,2 geometric algebra, also called the double conformal/Darboux cyclide geometric algebra (DCGA), has entities that represent conic sections. DCGA also has entities that represent planar sections of Darboux cyclides, which are called cyclidic sections in this paper. This paper presents these entities and many operations on them, in terms of algebraic expressions, computer code, and many examples of computer‐generated graphics. Operations include reflection, projection, rejection, and intersection with respect to spheres and planes. Other operations include rotation, translation, and dilation. Possible applications are introduced, which include orthographic and perspective projections of conic sections onto view planes, which may be of interest in computer graphics or other computational geometry subjects [ABSTRACT FROM AUTHOR]

Voxelization is a crucial process for many computer graphics applications such as collision detection, rendering of translucent objects, and global illumination. However, in some situations, although the mesh looks good, the voxelization resultmay be undesirable. In this paper,we describe a novel voxelizationmethod that uses the graphics processing unit for surface voxelization. Our improvements on the voxelization algorithm can address a problem of state-of-the-art voxelization, which cannot deal with thin parts of the mesh object.We improve the quality of voxelization on both normal mediation and surface correction. Furthermore, we investigate our voxelizationmethods on indirect illumination, showing the improvement on the quality of real-time rendering. [ABSTRACT FROM AUTHOR]

Terrain generation methods have long been divided between procedural and physically‐based. Procedural methods build upon the fast evaluation of a mathematical function but suffer from a lack of geological consistency, while physically‐based simulation enforces this consistency at the cost of thousands of iterations unraveling the history of the landscape. In particular, the simulation of the competition between tectonic uplift and fluvial erosion expressed by the stream power law raised recent interest in computer graphics as this allows the generation and control of consistent large‐scale mountain ranges, albeit at the cost of a lengthy simulation. In this paper, we explore the analytical solutions of the stream power law and propose a method that is both physically‐based and procedural, allowing fast and consistent large‐scale terrain generation. In our approach, time is no longer the stopping criterion of an iterative process but acts as the parameter of a mathematical function, a slider that controls the aging of the input terrain from a subtle erosion to the complete replacement by a fully formed mountain range. While analytical solutions have been proposed by the geomorphology community for the 1D case, extending them to a 2D heightmap proves challenging. We propose an efficient implementation of the analytical solutions with a multigrid accelerated iterative process and solutions to incorporate landslides and hillslope processes – two erosion factors that complement the stream power law. [ABSTRACT FROM AUTHOR]

The field of visual computing is rapidly advancing due to the emergence of generative artificial intelligence (AI), which unlocks unprecedented capabilities for the generation, editing, and reconstruction of images, videos, and 3D scenes. In these domains, diffusion models are the generative AI architecture of choice. Within the last year alone, the literature on diffusion‐based tools and applications has seen exponential growth and relevant papers are published across the computer graphics, computer vision, and AI communities with new works appearing daily on arXiv. This rapid growth of the field makes it difficult to keep up with all recent developments. The goal of this state‐of‐the‐art report (STAR) is to introduce the basic mathematical concepts of diffusion models, implementation details and design choices of the popular Stable Diffusion model, as well as overview important aspects of these generative AI tools, including personalization, conditioning, inversion, among others. Moreover, we give a comprehensive overview of the rapidly growing literature on diffusion‐based generation and editing, categorized by the type of generated medium, including 2D images, videos, 3D objects, locomotion, and 4D scenes. Finally, we discuss available datasets, metrics, open challenges, and social implications. This STAR provides an intuitive starting point to explore this exciting topic for researchers, artists, and practitioners alike. [ABSTRACT FROM AUTHOR]

In machine learning and computer graphics, a fundamental task is the approximation of a probability density function through a well‐dispersed collection of samples. Providing a formal metric for measuring the distance between probability measures on general spaces, Optimal Transport (OT) emerges as a pivotal theoretical framework within this context. However, the associated computational burden is prohibitive in most real‐world scenarios. Leveraging the simple structure of OT in 1D, Sliced Optimal Transport (SOT) has appeared as an efficient alternative to generate samples in Euclidean spaces. This paper pushes the boundaries of SOT utilization in computational geometry problems by extending its application to sample densities residing on more diverse mathematical domains, including the spherical space 핊d, the hyperbolic plane ℍd, and the real projective plane ℙd. Moreover, it ensures the quality of these samples by achieving a blue noise characteristic, regardless of the dimensionality involved. The robustness of our approach is highlighted through its application to various geometry processing tasks, such as the intrinsic blue noise sampling of meshes, as well as the sampling of directions and rotations. These applications collectively underscore the efficacy of our methodology. [ABSTRACT FROM AUTHOR]

The intricate physiological composition of the human face facilitates the manifestation of diverse facial expressions, serving as a conduit for the conveyance of emotions, cognitive states, and the anticipation of future reactions. This multifaceted ability holds paramount significance in character representation. The realistic reconstruction of 3D human facial expressions stands as a focal point within the realms of computer graphics and computer vision research. The endeavor to capture and reconstruct three‐dimensional models depicting facial expressions finds extensive utility across various domains, notably making notable strides in computer games, cinematic productions, medical applications, and social interaction paradigms. This paper directs its attention to the realm of facial animation capture, elucidating the evolution of its manifold techniques and their applications. Furthermore, a meticulous analysis of the distinctions between these techniques ensues, unraveling their respective merits and demerits. [ABSTRACT FROM AUTHOR]

ABSTRACT Developable surfaces have been extensively studied in computer graphics because they are involved in a large body of applications. This type of surfaces has also been used in computer vision and document processing in the context of three-dimensional (3D) reconstruction for book digitization and augmented reality. Indeed, the shape of a smoothly deformed piece of paper can be very well modeled by a developable surface. Most of the existing developable surface parameterizations do not handle boundaries or are driven by overly large parameter sets. These two characteristics become issues in the context of developable surface reconstruction from real observations. Our main contribution is a generative model of bounded developable surfaces that solves these two issues. Our model is governed by intuitive parameters whose number depends on the actual deformation and including the 'flat shape boundary'. A vast majority of the existing image-based paper 3D reconstruction methods either require a tightly controlled environment or restricts the set of possible deformations. We propose an algorithm for reconstructing our model's parameters from a general smooth 3D surface interpolating a sparse cloud of 3D points. The latter is assumed to be reconstructed from images of a static piece of paper or any other developable surface. Our 3D reconstruction method is well adapted to the use of keypoint matches over multiple images. In this context, the initial 3D point cloud is reconstructed by structure-from-motion for which mature and reliable algorithms now exist and the thin-plate spline is used as a general smooth surface model. After initialization, our model's parameters are refined with model-based bundle adjustment. We experimentally validated our model and 3D reconstruction algorithm for shape capture and augmented reality on seven real datasets. The first six datasets consist of multiple images or videos and a sparse set of 3D points obtained by structure-from-motion. The last dataset is a dense 3D point cloud acquired by structured light. Our implementation has been made publicly available on the authors' web home pages. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Analytical polygon‐based computer‐generated holography (CGH) is promising because of its fast rendering speed. However, quadrilateral‐based full‐analytical CGH is infeasible. In this paper, we proposed a novel analytical CGH rendering method for quadrilateral meshes, which is compatible with modern modeling software and can simultaneously reduce the rendering load. [ABSTRACT FROM AUTHOR]

Poisson's equation is one of the most popular partial differential equation (PDE), which is widely used in image processing, computer graphics and other fields. However, solving a large‐scale Poisson's equation always costs huge computational resources. Fast Fourier transform (FFT) is an efficient Poisson solver but it only works in rectangular domain. In this paper, we propose a FFT‐based Poisson solver in nonrectangular domain on regular grids combined with algebraic multigrid (AMG). We extend the original Poisson's equation to a rectangular domain to construct an equivalent equation, so that it can use FFT algorithm to accelerate the solving to Poisson's equation. Experiments show that the FFT‐based Poisson solver can improve the solving speed of large‐scale Poisson's equations in nonrectangular domain. We demonstrate the solver in applications of image processing and fluid simulation. [ABSTRACT FROM AUTHOR]

The Laplace Beltrami operator is one of the essential tools in geometric processing. It allows us to solve numerous partial differential equations on discrete surface meshes, which is a fundamental building block in many computer graphics applications. Discrete Laplacians are typically limited to standard elements like triangles or quadrilaterals, which severely constrains the tessellation of the mesh. But in recent years, several approaches were able to generalize the Laplace Beltrami and its closely related gradient and divergence operators to more general meshes. This allows artists and engineers to work with a wider range of elements which are sometimes required and beneficial in their field. This paper discusses the different constructions of these three ubiquitous differential operators on arbitrary polygons and analyzes their individual advantages and properties in common computer graphics applications. [ABSTRACT FROM AUTHOR]

Facial makeup enriches the beauty of not only real humans but also virtual characters; therefore, makeup for 3D facial models is highly in demand in productions. However, painting directly on 3D faces and capturing real‐world makeup are costly, and extracting makeup from 2D images often struggles with shading effects and occlusions. This paper presents the first method for extracting makeup for 3D facial models from a single makeup portrait. Our method consists of the following three steps. First, we exploit the strong prior of 3D morphable models via regression‐based inverse rendering to extract coarse materials such as geometry and diffuse/specular albedos that are represented in the UV space. Second, we refine the coarse materials, which may have missing pixels due to occlusions. We apply inpainting and optimization. Finally, we extract the bare skin, makeup, and an alpha matte from the diffuse albedo. Our method offers various applications for not only 3D facial models but also 2D portrait images. The extracted makeup is well‐aligned in the UV space, from which we build a large‐scale makeup dataset and a parametric makeup model for 3D faces. Our disentangled materials also yield robust makeup transfer and illumination‐aware makeup interpolation/removal without a reference image. [ABSTRACT FROM AUTHOR]

Despite the rapid development and proliferation of computer graphics hardware devices for scene capture in the most recent decade, the high‐resolution 3D/4D acquisition of gaseous scenes (e.g., smokes) in real time remains technically challenging in graphics research nowadays. In this paper, we explore a hybrid approach to simultaneously taking advantage of both the model‐centric method and the data‐driven method. Specifically, this paper develops a novel conditional generative model to rapidly reconstruct the temporal density and velocity fields of gaseous phenomena based on the sequence of two projection views. With the data‐driven method, we can achieve the strong coupling of density update and the estimation of flow motion, as a result, we can greatly improve the reconstruction performance for smoke scenes. First, we employ a conditional generative network to generate the initial density field from input projection views and estimate the flow motion based on the adjacent frames. Second, we utilize the differentiable advection layer and design a velocity estimation network with the long‐term mechanism to help achieve the end‐to‐end training and more stable graphics effects. Third, we can re‐simulate the input scene with flexible coupling effects based on the estimated velocity field subject to artists' guidance or user interaction. Moreover, our generative model could accommodate single projection view as input. In practice, more input projection views are enabling and facilitating the high‐fidelity reconstruction with more realistic and finer details. We have conducted extensive experiments to confirm the effectiveness, efficiency, and robustness of our new method compared with the previous state‐of‐the‐art techniques. [ABSTRACT FROM AUTHOR]

The generation of a concise building model has been and continues to be a challenge in photogrammetry and computer graphics. The current methods typically focus on the simplicity and fidelity of the model, but those methods either fail to preserve the structural information or suffer from low computational efficiency. In this paper, we propose a novel method to generate concise building models from dense meshes by extracting and completing the planar primitives of the building. From the perspective of probability, we first extract planar primitives from the input mesh and obtain the adjacency relationships between the primitives. Since primitive loss and structural defects are inevitable in practice, we employ a novel structural completion approach to eliminate linkage errors. Finally, the concise polygonal mesh is reconstructed by connectivity‐based primitive assembling. Our method is efficient and robust to various challenging data. Experiments on various building models revealed the efficacy and applicability of our method. [ABSTRACT FROM AUTHOR]

In the last decade, the extensive introduction of LED lighting sources has brought elements of innovation to interior lighting design in terms of color. Besides the new tunable white LED source, lighting is no longer exclusively white; indeed, colored lighting has entered the design practice thanks to the positive effects on people's health and mood. Unfortunately, this element of lighting innovation, color, cannot be computed correctly in commercial lighting design software. These computations are based on the assumption that light is only white or defined in terms of RGB triplets in the relative digital color space of computer graphics, which does not have a physically correct relationship with the actual spectral power distribution (SPD) of luminaires. In this paper, attention is focused on a practical design‐oriented approach for describing luminaires in lighting design software that also considers the real SPD and the luminous intensity distribution. The focus is on information available to lighting designers who do not have a laboratory to measure light sources and luminaires. This information could be available in online datasheets or as a Cartesian graph from luminaires and light sources manufacturers. Following this approach, a set of functions is proposed that can be easily implemented in lighting design software to improve light sources' color management and allow lighting designers to add SPD data to luminaires. [ABSTRACT FROM AUTHOR]