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Item Enhancing Medical Diagnosis and Treatment Planning through Automated Acquisition and Classification of Bone Fracture Patterns(The Eurographics Association, 2024) Pérez-Cano, Francisco Daniel; Parra-Cabrera, Gema; Camacho-García, Rubén; Jiménez, Juan José; Marco, Julio; Patow, GustavoThe extraction of the main features of a fractured bone area enables subsequent virtual reproduction for bone simulations. Exploring the fracture zone for other applications remains largely unexplored in current research. Recreating and analyzing fracture patterns has direct applications in medical training programs for traumatologists, automatic bone fracture reduction algorithms, and diagnostics. Furthermore, pattern classification aids in establishing treatment guidelines that specialists can follow during the surgical process. This paper focuses on the process of obtaining an accurate representation of bone fractures, starting with computed tomography scans, and subsequently classifying these patterns using a convolutional neural network. The proposed methodology aims to streamline the extraction and classification of fractures from clinical cases, contributing to enhanced diagnosis and medical simulation applications.Item Simulation of Mechanical Weathering for Modeling Rocky Terrains(The Eurographics Association, 2024) Mateos, Diego; Carranza, Luis; Susin, Anton; Argudo, Oscar; Marco, Julio; Patow, GustavoSynthetic terrains play a vital role in various applications, including entertainment, training, and simulation. This work focuses on rocky terrains akin to those found in alpine environments, which contain many complex features such as sharp ridges, loose blocks, or overhangs that are often inadequately represented by standard 2D elevation maps. We propose a novel method based on a simplified simulation of mechanical erosion processes commonly observed in high-altitude terrains, in particular the weathering due to freeze-thaw cycles. The ultimate objective is to generate plausible rocky geometry from existing 3D models, as well as account for the temporal evolution due to these weathering processes. Additionally, we have developed an artist-friendly tool integrated as an add-on into Blender.Item Adaptation of Interaction Mechanisms in Virtual Reality Shopping Environments for People with Upper Limb Motor Difficulties(The Eurographics Association, 2024) Grande, Rubén; Herrera, Vanesa; Glez-Morcillo, Carlos; Reyes, Ana de los; Castro-Schez, José J.; Albusac, Javier; Marco, Julio; Patow, Gustavo; Grande, Rubén|https://orcid.org/0000-0002-0583-6865; Herrera, Vanesa|https://orcid.org/0000-0002-6187-4794; Glez-Morcillo, Carlos|https://orcid.org/0000-0002-8568-9542; Reyes, Ana de los|https://orcid.org/0000-0003-2905-2405; Castro-Schez, José J.|https://orcid.org/0000-0002-0201-7653; Albusac, Javier|https://orcid.org/0000-0003-1889-3065In recent years, there has been research and exploration into the development of new shopping experiences within the field of electronic commerce (e-commerce). One of the technologies that can offer a more immersive shopping experience is Virtual Reality (VR). Retail giants such as Amazon and Alibaba Group have begun to use it. The technological advancement of VR, motivated by its use in various domains like e-commerce, has driven the development of software tools like APIs which allow developers to easily develop applications for these devices. One of the latest technologies included in recent VR headsets is hand tracking, which allows users to use their own hands as an input method to interact with the virtual environment. However, software tools for the development of VR applications are not fully adapted to include accessibility options for people with motor difficulties in their bodies, making it very difficult for these people to use this technology with both controllers and hand tracking. To promote accessibility options in the use of VR shopping environments, this study will present the adaptation of a set of interaction mechanisms, among which we highlight: automatic object grabbing, release of grabbed objects, navigation through the environment, attraction of distant objects, and interaction with the shopping cart. These adaptations will be made using Meta's API for Meta Quest devices as a base. The adapted environment has been tested by healthy students from the faculty and one of them with reduced mobility in the left half of his body after suffering a stroke. In this paper, we present the feedback provided by the volunteers, as well as the verification that these interaction mechanisms meet our expectations. This is an essential previous step to carry out a planned experimental session with patients with spinal cord injuries and therapist at the National Hospital for Paraplegics in Toledo (HNPT).Item Computing Manifold Next-Event Estimation without Derivatives using the Nelder-Mead Method(The Eurographics Association, 2024) Granizo-Hidalgo, Ana; Holzschuch, Nicolas; Haines, Eric; Garces, ElenaSpecular surfaces, by focusing the light that is being reflected or refracted, cause bright spots in the scene, called caustics. These caustics are challenging to compute for global illumination algorithms. Manifold-based methods (Manifold Exploration, Manifold Next-Event Estimation, Specular Next Event Estimation) compute these caustics as the zeros of an objective function, using the Newton-Raphson method. They are efficient, but require computing the derivatives of the objective function, which in turn requires local surface derivatives around the reflection point, which can be challenging to implement. In this paper, we leverage the Nelder-Mead method to compute caustics using Manifold Next-Event Estimation without having to compute local derivatives. Our method only requires local evaluations of the objective function, making it an easy addition to any path-tracing algorithm.Item Path Sampling Methods for Differentiable Rendering(The Eurographics Association, 2024) Su, Tanli; Gkioulekas, Ioannis; Haines, Eric; Garces, ElenaWe introduce a suite of path sampling methods for differentiable rendering of scene parameters that do not induce visibility-driven discontinuities, such as BRDF parameters. We begin by deriving a path integral formulation for differentiable rendering of such parameters, which we then use to derive methods that importance sample paths according to this formulation. Our methods are analogous to path tracing and path tracing with next event estimation for primal rendering, have linear complexity, and can be implemented efficiently using path replay backpropagation. Our methods readily benefit from differential BRDF sampling routines, and can be further enhanced using multiple importance sampling and a loss-aware pixel-space adaptive sampling procedure tailored to our path integral formulation. We show experimentally that our methods reduce variance in rendered gradients by potentially orders of magnitude, and thus help accelerate inverse rendering optimization of BRDF parameters.Item Does Higher Refractive Index Mean Higher Gloss?(The Eurographics Association, 2024) Gigilashvili, Davit; Diaz Estrada, David Norman; Haines, Eric; Garces, ElenaAccording to Fresnel equations, the amount of specular reflection at the dielectric surface depends on two factors: incident angle and the difference in refractive indices of inner and outer media. Therefore, it is often assumed that the higher the refractive index of the material, the glossier it looks. However, gloss perception is a complex process that, in addition to specular reflectance, depends on many other factors, such as object's translucency and shape. In this study, we conducted two psychophysical experiments to quantify the impact of refractive index on perceived gloss for objects with varying degrees of translucency and surface roughness. For some objects a monotonic positive relationship between refractive index and perceived gloss was observed, while for others the relationship was found to be non-monotonic. Afterward, we evaluated how the refractive index affects image cues to gloss and tried to explain psychophysical results by image statistics.Item Robust Cone Step Mapping(The Eurographics Association, 2024) Bán, Róbert; Valasek, Gábor; Bálint, Csaba; Vad, Viktor A.; Haines, Eric; Garces, ElenaPer-pixel displacement mapping provides an alternative to high-fidelity geometry and flat textured faces with in-between performance costs. Although cone maps are known to facilitate efficient and robust rendering of height fields, we show that these cannot guarantee robustness under bilinear interpolation, and we propose corrections to this issue. First, we define an artifactfree minimum step size for the cone map tracing algorithm while remaining comparable in performance to that of Dummer. Second, we modify the cone map generation procedure so that at bilinearly interpolated values the unbounding cones remain disjoint from the heightmap, thereby preventing another source of rendering artifacts. Third, we introduce an exact method to generate relaxed cones such that any ray within intersects the heightmap at most once, in contrast to the original algorithm that is both computationally more expensive and generates incorrect relaxed cones. Finally, we demonstrate the applicability of these algorithm improvements with visual and performance comparisons in our C++ and HLSL implementation.Item Self-Supervised Multi-Layer Garment Animation Generation Network(The Eurographics Association, 2024) Han, Guoqing; Shi, Min; Mao, Tianlu; Wang, Xinran; Zhu, Dengming; Gao, Lin; Chen, Renjie; Ritschel, Tobias; Whiting, EmilyThis paper presents a self-supervised multi-layer garment animation generation network. The complexity inherent in multi-layer garments, particularly the diverse interactions between layers, poses challenges in generating continuous, stable, physically accurate, and visually realistic garment deformation animations. To tackle these challenges, we present the Self-Supervised Multi-Layer Garment Animation Generation Network (SMLN). The architecture of SMLN is based on graph neural networks, which represents garment models uniformly as graph structures, thereby naturally depicting the hierarchical structure of garments and capturing the relationships between garment layers. Unlike existing multi-layer garment deformation methods, we model interaction forces such as friction and repulsion between garment layers, translating physical laws consistent with dynamics into network constraints. We penalize garment deformation regions that exceed these constraints. Furthermore, instead of the traditional post-processing method of fixed vertex displacement calculation for handling collision interactions, we add an additional repulsion constraint layer within the network to update the corresponding repulsive force acceleration, thereby adaptively managing collisions between garment layers. Our self-supervised modeling approach enables the network to learn without relying on garment sample datasets. Experimental results demonstrate that our method is capable of generating visually plausible multi-layer garment deformation effects, surpassing existing methods in both visual quality and evaluation metrics.Item Self-Supervised Multi-Layer Garment Animation Generation Network(The Eurographics Association, 2024) Han, Guoqing; Shi, Min; Mao, Tianlu; Wang, Xinran; Zhu, Dengming; Gao, Lin; Chen, Renjie; Ritschel, Tobias; Whiting, EmilyThis paper presents a self-supervised multi-layer garment animation generation network. The complexity inherent in multi-layer garments, particularly the diverse interactions between layers, poses challenges in generating continuous, stable, physically accurate, and visually realistic garment deformation animations. To tackle these challenges, we present the Self-Supervised Multi-Layer Garment Animation Generation Network (SMLN). The architecture of SMLN is based on graph neural networks, which represents garment models uniformly as graph structures, thereby naturally depicting the hierarchical structure of garments and capturing the relationships between garment layers. Unlike existing multi-layer garment deformation methods, we model interaction forces such as friction and repulsion between garment layers, translating physical laws consistent with dynamics into network constraints. We penalize garment deformation regions that exceed these constraints. Furthermore, instead of the traditional post-processing method of fixed vertex displacement calculation for handling collision interactions, we add an additional repulsion constraint layer within the network to update the corresponding repulsive force acceleration, thereby adaptively managing collisions between garment layers. Our self-supervised modeling approach enables the network to learn without relying on garment sample datasets. Experimental results demonstrate that our method is capable of generating visually plausible multi-layer garment deformation effects, surpassing existing methods in both visual quality and evaluation metrics.Item Navigating the Manifold of Translucent Appearance(The Eurographics Association and John Wiley & Sons Ltd., 2024) Lanza, Dario; Masia, Belen; Jarabo, Adrian; Bermano, Amit H.; Kalogerakis, EvangelosWe present a perceptually-motivated manifold for translucent appearance, designed for intuitive editing of translucent materials by navigating through the manifold. Classic tools for editing translucent appearance, based on the use of sliders to tune a number of parameters, are challenging for non-expert users: These parameters have a highly non-linear effect on appearance, and exhibit complex interplay and similarity relations between them. Instead, we pose editing as a navigation task in a low-dimensional space of appearances, which abstracts the user from the underlying optical parameters. To achieve this, we build a low-dimensional continuous manifold of translucent appearance that correlates with how humans perceive this type of materials. We first analyze the correlation of different distance metrics in image space with human perception. We select the best-performing metric to build a low-dimensional manifold, which can be used to navigate the space of translucent appearance. To evaluate the validity of our proposed manifold within its intended application scenario, we build an editing interface that leverages the manifold, and relies on image navigation plus a fine-tuning step to edit appearance. We compare our intuitive interface to a traditional, slider-based one in a user study, demonstrating its effectiveness and superior performance when editing translucent objects.
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