EG2023

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https://diglib.eg.org/handle/10.2312/2633296

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Efficient Needle Insertion Simulation using Hybrid Constraint Solver and Isolated DOFs
(The Eurographics Association, 2023) Martin, Claire; Zeng, Ziqiu; Courtecuisse, Hadrien; Babaei, Vahid; Skouras, Melina
This paper introduces a real-time compatible method to improve the location of constraints between a needle and tissues in the context of needle insertion simulation. This method is based on intersections between the Finite Element (FE) meshes of the needle and the tissues. It is coupled with the method of isolating mechanical DOFs and a hybrid solver (implying both direct and iterative resolutions) to respectively generate and solve the constraint problem while reducing the computation time.
Velocity-Based LOD Reduction in Virtual Reality: A Psychophysical Approach
(The Eurographics Association, 2023) Petrescu, David; Warren, Paul A.; Montazeri, Zahra; Pettifer, Steve; Babaei, Vahid; Skouras, Melina
Virtual Reality headsets enable users to explore the environment by performing self-induced movements. The retinal velocity produced by such motion reduces the visual system's ability to resolve fine detail. We measured the impact of self-induced head rotations on the ability to detect quality changes of a realistic 3D model in an immersive virtual reality environment. We varied the Level of Detail (LOD) as a function of rotational head velocity with different degrees of severity. Using a psychophysical method, we asked 17 participants to identify which of the two presented intervals contained the higher quality model under two different maximum velocity conditions. After fitting psychometric functions to data relating the percentage of correct responses to the aggressiveness of LOD manipulations, we identified the threshold severity for which participants could reliably (75%) detect the lower LOD model. Participants accepted an approximately four-fold LOD reduction even in the low maximum velocity condition without a significant impact on perceived quality, suggesting that there is considerable potential for optimisation when users are moving (increased range of perceptual uncertainty). Moreover, LOD could be degraded significantly more (around 84%) in the maximum head velocity condition, suggesting these effects are indeed speed-dependent.
Automatic Step Size Relaxation in Sphere Tracing
(The Eurographics Association, 2023) Bán, Róbert; Valasek, Gábor; Babaei, Vahid; Skouras, Melina
We propose a robust auto-relaxed sphere tracing method that automatically scales its step sizes based on data from previous iterations. It possesses a scalar hyperparemeter that is used similarly to the learning rate of gradient descent methods. We show empirically that this scalar degree of freedom has a smaller effect on performance than the step-scale hyperparameters of concurrent sphere tracing variants. Additionally, we compare the performance of our algorithm to these both on procedural and discrete signed distance input and show that it outperforms or performs up to par to the most efficient method, depending on the limit on iteration counts. We also verify that our method takes significantly fewer robustness-preserving sphere trace fallback steps, as it generates fewer invalid, over-relaxed step sizes.
Guiding Light Trees for Many-Light Direct Illumination
(The Eurographics Association, 2023) Hamann, Eric; Jung, Alisa; Dachsbacher, Carsten; Babaei, Vahid; Skouras, Melina
Path guiding techniques reduce the variance in path tracing by reusing knowledge from previous samples to build adaptive sampling distributions. The Practical Path Guiding (PPG) approach stores and iteratively refines an approximation of the incident radiance field in a spatio-directional data structure that allows sampling the incident radiance. However, due to the limited resolution in both spatial and directional dimensions, this discrete approximation is not able to accurately capture a large number of very small lights. We present an emitter sampling technique to guide next event estimation (NEE) with a global light tree and adaptive tree cuts that integrates into the PPG framework. In scenes with many lights our technique significantly reduces the RMSE compared to PPG with uniform NEE, while adding close to no overhead in scenes with few light sources. The results show that our technique can also aid the incident radiance learning of PPG in scenes with difficult visibility.
Quick-Pro-Build: A Web-based Approach for Quick Procedural 3D Reconstructions of Buildings
(The Eurographics Association, 2023) Bohlender, Bela; Mühlhäuser, Max; Guinea, Alejandro Sanchez; Babaei, Vahid; Skouras, Melina
We present Quick-Pro-Build, a web-based approach for quick procedural 3D reconstruction of buildings. Our approach allows users to quickly and easily create realistic 3D models using two integrated reference views: street view and satellite view. We introduce a novel conditional and stochastic shape grammar to represent the procedural models based on the well-established CGA shape grammar. Based on our grammar and user interface, we propose 3 modalities for procedural modeling: 1) model from scratch, 2) copy, paste, and adapt, and 3) summarize, select and adapt. The third modality enables users to model a building by summarizing similar models into an architectural style description, selecting a model from the style description, and adapting it to the target building. Summarizing and selecting allows the third modality to be the most efficient option when modeling a building with a style similar to existing buildings. The third modality is enabled by a novel algorithm that can find and combine similarities from procedural models into a style description and allows learning the preference of the users for one model inside the style description.
EUROGRAPHICS 2023: Short Papers Frontmatter
(Eurographics Association, 2023) Babaei, Vahid; Skouras, Melina; Babaei, Vahid; Skouras, Melina
A Survey of Indicators for Mesh Quality Assessment
(The Eurographics Association and John Wiley & Sons Ltd., 2023) Sorgente, Tommaso; Biasotti, Silvia; Manzini, Gianmarco; Spagnuolo, Michela; Bousseau, Adrien; Theobalt, Christian
We analyze the joint efforts made by the geometry processing and the numerical analysis communities in the last decades to define and measure the concept of ''mesh quality''. Researchers have been striving to determine how, and how much, the accuracy of a numerical simulation or a scientific computation (e.g., rendering, printing, modeling operations) depends on the particular mesh adopted to model the problem, and which geometrical features of the mesh most influence the result. The goal was to produce a mesh with good geometrical properties and the lowest possible number of elements, able to produce results in a target range of accuracy. We overview the most common quality indicators, measures, or metrics that are currently used to evaluate the goodness of a discretization and drive mesh generation or mesh coarsening/refinement processes. We analyze a number of local and global indicators, defined over two- and three-dimensional meshes with any type of elements, distinguishing between simplicial, quadrangular/hexahedral, and generic polytopal elements. We also discuss mesh optimization algorithms based on the above indicators and report common libraries for mesh analysis and quality-driven mesh optimization.
A Survey of Optimal Transport for Computer Graphics and Computer Vision
(The Eurographics Association and John Wiley & Sons Ltd., 2023) Bonneel, Nicolas; Digne, Julie; Bousseau, Adrien; Theobalt, Christian
Optimal transport is a long-standing theory that has been studied in depth from both theoretical and numerical point of views. Starting from the 50s this theory has also found a lot of applications in operational research. Over the last 30 years it has spread to computer vision and computer graphics and is now becoming hard to ignore. Still, its mathematical complexity can make it difficult to comprehend, and as such, computer vision and computer graphics researchers may find it hard to follow recent developments in their field related to optimal transport. This survey first briefly introduces the theory of optimal transport in layman's terms as well as most common numerical techniques to solve it. More importantly, it presents applications of these numerical techniques to solve various computer graphics and vision related problems. This involves applications ranging from image processing, geometry processing, rendering, fluid simulation, to computational optics, and many more. It is aimed at computer graphics researchers desiring to follow optimal transport research in their field as well as optimal transport researchers willing to find applications for their numerical algorithms.
Is Drawing Order Important?
(The Eurographics Association, 2023) Qiu, Sherry; Wang, Zeyu; McMillan, Leonard; Rushmeier, Holly; Dorsey, Julie; Babaei, Vahid; Skouras, Melina
The drawing process is crucial to understanding the final result of a drawing. There has been a long history of understanding human drawing; what kinds of strokes people use and where they are placed. An area of interest in Artificial Intelligence is developing systems that simulate human behavior in drawing. However, there has been little work done to understand the order of strokes in the drawing process. Without sufficient understanding of natural drawing order, it is difficult to build models that can generate natural drawing processes. In this paper, we present a study comparing multiple types of stroke orders to confirm findings from previous work and demonstrate that multiple orderings of the same set of strokes can be perceived as human-drawn and different stroke order types achieve different perceived naturalness depending on the type of image prompt.
DropSPH: ISPH Simulation of Droplet Interactions with a Solid Surface
(The Eurographics Association, 2023) Keshtkar, Hossein; Aburumman, Nadine; Singh, Gurprit; Chu, Mengyu (Rachel)
We present a physically-based model to simulate droplet behaviours when impacted on a solid surface. Our model creates the coalescence, spreading, and break-up deformations that occur when a liquid droplet collides with a solid surface. We model the attraction-repulsion forces within an improved free surface Incompressible Smoothed Particle Hydrodynamics (ISPH) framework that includes contact force and cohesion force between particles. The results show that our model is effective in simulating several small-scale liquid phenomena.
Modern High Dynamic Range Imaging at the Time of Deep Learning
(The Eurographics Association, 2023) Banterle, Francesco; Artusi, Alessandro; Serrano, Ana; Slusallek, Philipp
In this tutorial, we introduce how the High Dynamic Range (HDR) imaging field has evolved in this new era where machine learning approaches have become dominant. The main reason of this success is that the use of machine learning and deep learning have automatized many tedious tasks achieving high-quality results overperforming classic methods. After an introduction on classic HDR imaging and its open problem, we will summarize the main approaches for: merging of multiple exposures, single image reconstructions or inverse tone mapping, tone mapping, and display visualization. Finally, we will highlights the still open problems in this machine learning era, and possible direction on how to solve them.
PointCloudSlicer: Gesture-based Segmentation of Point Clouds
(The Eurographics Association, 2023) Gowtham, Hari Hara; Parakkat, Amal Dev; Cani, Marie-Paule; Babaei, Vahid; Skouras, Melina
Segmentation is a fundamental problem in point-cloud processing, addressing points classification into consistent regions, the criteria for consistency being based on the application. In this paper, we introduce a simple, interactive framework enabling the user to quickly segment a point cloud in a few cutting gestures in a perceptually consistent way. As the user perceives the limit of a shape part, they draw a simple separation stroke over the current 2D view. The point cloud is then segmented without needing any intermediate meshing step. Technically, we find an optimal, perceptually consistent cutting plane constrained by user stroke and use it for segmentation while automatically restricting the extent of the cut to the closest shape part from the current viewpoint. This enables users to effortlessly segment complex point clouds from an arbitrary viewpoint with the possibility of handling self-occlusions.
Project Elements: A Computational Entity-component-system in a Scene-graph Pythonic Framework, for a Neural, Geometric Computer Graphics Curriculum
(The Eurographics Association, 2023) Papagiannakis, George; Kamarianakis, Manos; Protopsaltis, Antonis; Angelis, Dimitris; Zikas, Paul; Magana, Alejandra; Zara, Jiri
We present the Elements project, a lightweight, open-source, computational science and computer graphics (CG) framework, tailored for educational needs, that offers, for the first time, the advantages of an Entity-Component-System (ECS) along with the rapid prototyping convenience of a Scenegraph-based pythonic framework. This novelty allows advances in the teaching of CG: from heterogeneous directed acyclic graphs and depth-first traversals, to animation, skinning, geometric algebra and shader-based components rendered via unique systems all the way to their representation as graph neural networks for 3D scientific visualization. Taking advantage of the unique ECS in a a Scenegraph underlying system, this project aims to bridge CG curricula and modern game engines (MGEs), that are based on the same approach but often present these notions in a black-box approach. It is designed to actively utilize software design patterns, under an extensible open-source approach. Although Elements provides a modern (i.e., shader-based as opposed to fixed-function OpenGL), simple to program approach with Jupyter notebooks and unit-tests, its CG pipeline is not black-box, exposing for teaching for the first time unique challenging scientific, visual and neural computing concepts.
Game-based Transformations: A Playful Approach to Learning Transformations in Computer Graphics
(The Eurographics Association, 2023) Eisemann, Martin; Magana, Alejandra; Zara, Jiri
In this paper, we present a playful and game-based learning approach to teaching transformations in a second-year undergraduate computer graphics course. While the theoretical concepts were taught in class, the exercise consists of two web-based tools that help the students to get a playful grasp on the complex topic, which is the foundation for many of the later concepts typically taught in computer graphics, such as the rendering pipeline, animation, camera motion, shadow mapping and many more. The final students' projects and feedback indicate that the game-based introduction was well-received by the students.
Towards L-System Captioning for Tree Reconstruction
(The Eurographics Association, 2023) Magnusson, Jannes S.; Hilsmann, Anna; Eisert, Peter; Babaei, Vahid; Skouras, Melina
This work proposes a novel concept for tree and plant reconstruction by directly inferring a Lindenmayer-System (L-System) word representation from image data in an image captioning approach. We train a model end-to-end which is able to translate given images into L-System words as a description of the displayed tree. To prove this concept, we demonstrate the applicability on 2D tree topologies. Transferred to real image data, this novel idea could lead to more efficient, accurate and semantically meaningful tree and plant reconstruction without using error-prone point cloud extraction, and other processes usually utilized in tree reconstruction. Furthermore, this approach bypasses the need for a predefined L-System grammar and enables species-specific L-System inference without biological knowledge.
Non-Separable Multi-Dimensional Network Flows for Visual Computing
(The Eurographics Association, 2023) Ehm, Viktoria; Cremers, Daniel; Bernard, Florian; Singh, Gurprit; Chu, Mengyu (Rachel)
Flows in networks (or graphs) play a significant role in numerous computer vision tasks. The scalar-valued edges in these graphs often lead to a loss of information and thereby to limitations in terms of expressiveness. For example, oftentimes highdimensional data (e.g. feature descriptors) are mapped to a single scalar value (e.g. the similarity between two feature descriptors). To overcome this limitation, we propose a novel formalism for non-separable multi-dimensional network flows. By doing so, we enable an automatic and adaptive feature selection strategy - since the flow is defined on a per-dimension basis, the maximizing flow automatically chooses the best matching feature dimensions. As a proof of concept, we apply our formalism to the multi-object tracking problem and demonstrate that our approach outperforms scalar formulations on the MOT16 benchmark in terms of robustness to noise.
Effective User Studies in Computer Graphics
(The Eurographics Association, 2023) Malpica, Sandra; Sun, Qi; Kellnhofer, Petr; Beacco, Alejandro; Senel, Gizem; McDonnell, Rachel; Flores Vargas, Mauricio; Serrano, Ana; Slusallek, Philipp
User studies are a useful tool for researchers, allowing them to collect data on how users perceive, interact with and process different types of sensory information. If planned in advance, user experiments can be leveraged in every stage of a research project, from early design, prototyping and feature exploration to applied proofs of concept, passing through validation and data collection for model training. User studies can provide the researcher with different types of information depending on the chosen methodology: user performance metrics, surveys and interviews, field studies, physiological data, etc. Considering human perception and other cognitive processes is particularly important in computer graphics, where most research produces outputs whose ultimate purpose is to be seen or perceived by a human. Being able to measure in an objective and systematic way how the information we generate is integrated into the representational space humans create to situate themselves in the world means that researchers will have more information to implement optimal algorithms, tools and techniques. In this tutorial we will give an overview of good practices for user studies in computer graphics with a particular focus on virtual reality use cases. We will cover the basics on how to design, carry out and analyze good user studies, as well as different particularities to be taken into account in immersive environments.
Towards a Formal Education of Visual Effects Artists
(The Eurographics Association, 2023) Redford, Adam; Anderson, Eike Falk; Magana, Alejandra; Zara, Jiri
The rapid growth of the visual effects industry over the past three decades and increasing demand for high quality visual effects for film, television and similar media, in turn increasing demand for graduates in this field have highlighted the need for formal education in visual effects. In this paper, we explore the design of a visual effects undergraduate degree programme and discuss our aims and objectives in implementing this programme in terms of both curriculum and syllabus.
Neurosymbolic Models for Computer Graphics
(The Eurographics Association and John Wiley & Sons Ltd., 2023) Ritchie, Daniel; Guerrero, Paul; Jones, R. Kenny; Mitra, Niloy J.; Schulz, Adriana; Willis, Karl D. D.; Wu, Jiajun; Bousseau, Adrien; Theobalt, Christian
Procedural models (i.e. symbolic programs that output visual data) are a historically-popular method for representing graphics content: vegetation, buildings, textures, etc. They offer many advantages: interpretable design parameters, stochastic variations, high-quality outputs, compact representation, and more. But they also have some limitations, such as the difficulty of authoring a procedural model from scratch. More recently, AI-based methods, and especially neural networks, have become popular for creating graphic content. These techniques allow users to directly specify desired properties of the artifact they want to create (via examples, constraints, or objectives), while a search, optimization, or learning algorithm takes care of the details. However, this ease of use comes at a cost, as it's often hard to interpret or manipulate these representations. In this state-of-the-art report, we summarize research on neurosymbolic models in computer graphics: methods that combine the strengths of both AI and symbolic programs to represent, generate, and manipulate visual data. We survey recent work applying these techniques to represent 2D shapes, 3D shapes, and materials & textures. Along the way, we situate each prior work in a unified design space for neurosymbolic models, which helps reveal underexplored areas and opportunities for future research.
Tight Bounding Boxes for Voxels and Bricks in a Signed Distance Field Ray Tracer
(The Eurographics Association, 2023) Hansson-Söderlund, Herman; Akenine-Möller, Tomas; Babaei, Vahid; Skouras, Melina
We present simple methods to compute tight axis-aligned bounding boxes for voxels and for bricks of voxels in a signed distance function renderer based on ray tracing. Our results show total frame time reductions of 20-31% in a real-time path tracer.

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