36-Issue 8
Permanent URI for this collection
Browse
Browsing 36-Issue 8 by Subject "animation"
Now showing 1 - 5 of 5
Results Per Page
Sort Options
Item Detail‐Preserving Explicit Mesh Projection and Topology Matching for Particle‐Based Fluids(© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Dagenais, F.; Gagnon, J.; Paquette, E.; Chen, Min and Zhang, Hao (Richard)We propose a new explicit surface tracking approach for particle‐based fluid simulations. Our goal is to advect and update a highly detailed surface, while only computing a coarse simulation. Current explicit surface methods lose surface details when projecting on the isosurface of an implicit function built from particles. Our approach uses a detail‐preserving projection, based on a signed distance field, to prevent the divergence of the explicit surface without losing its initial details. Furthermore, we introduce a novel topology matching stage that corrects the topology of the explicit surface based on the topology of an implicit function. To that end, we introduce an optimization approach to update our explicit mesh signed distance field before remeshing. Our approach is successfully used to preserve the surface details of melting and highly viscous objects, and shown to be stable by handling complex cases involving multiple topological changes. Compared to the computation of a high‐resolution simulation, using our approach with a coarse fluid simulation significantly reduces the computation time and improves the quality of the resulting surface.We propose a new explicit surface tracking approach for particle‐based fluid simulations. Our goal is to advect and update a highly detailed surface, while only computing a coarse simulation. Current explicit surface methods lose surface details when projecting on the isosurface of an implicit function built from particles. Our approach uses a detail‐preserving projection, based on a signed distance field, to prevent the divergence of the explicit surface without losing its initial details. Furthermore, we introduce a novel topology matching stage that corrects the topology of the explicit surface based on the topology of an implicit function. To that end, we introduce an optimization approach to update our explicit mesh signed distance field before remeshing.Item DYVERSO: A Versatile Multi‐Phase Position‐Based Fluids Solution for VFX(© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Alduán, Iván; Tena, Angel; Otaduy, Miguel A.; Chen, Min and Zhang, Hao (Richard)Many impressive fluid simulation methods have been presented in research papers before. These papers typically focus on demonstrating particular innovative features, but they do not meet in a comprehensive manner the production demands of actual VFX pipelines. VFX artists seek methods that are flexible, efficient, robust and scalable, and these goals often conflict with each other. In this paper, we present a multi‐phase particle‐based fluid simulation framework, based on the well‐known Position‐Based Fluids (PBF) method, designed to address VFX production demands. Our simulation framework handles multi‐phase interactions robustly thanks to a modified constraint formulation for density contrast PBF. And, it also supports the interaction of fluids sampled at different resolutions. We put special care on data structure design and implementation details. Our framework highlights cache‐efficient GPU‐friendly data structures, an improved spatial voxelization technique based on Z‐index sorting, tuned‐up simulation algorithms and two‐way‐coupled collision handling based on VDB fields. Altogether, our fluid simulation framework empowers artists with the efficiency, scalability and versatility needed for simulating very diverse scenes and effects.Many impressive fluid simulation methods have been presented in research papers before. These papers typically focus on demonstrating particular innovative features, but they do not meet in a comprehensive manner the production demands of actual VFX pipelines. VFX artists seek methods that are flexible, efficient, robust and scalable, and these goals often conflict with each other. In this paper, we present a multi‐phase particle‐based fluid simulation framework, based on the well‐known Position‐Based Fluids (PBF) method, designed to address VFX production demands.Item EACS: Effective Avoidance Combination Strategy(© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Bruneau, J.; Pettré, J.; Chen, Min and Zhang, Hao (Richard)When navigating in crowds, humans are able to move efficiently between people. They look ahead to know which path would reduce the complexity of their interactions with others. Current navigation systems for virtual agents consider long‐term planning to find a path in the static environment and short‐term reactions to avoid collisions with close obstacles. Recently some mid‐term considerations have been added to avoid high density areas. However, there is no mid‐term planning among static and dynamic obstacles that would enable the agent to look ahead and avoid difficult paths or find easy ones as humans do. In this paper, we present a system for such mid‐term planning. This system is added to the navigation process between pathfinding and local avoidance to improve the navigation of virtual agents. We show the capacities of such a system using several case studies. Finally we use an energy criterion to compare trajectories computed with and without the mid‐term planning.When navigating in crowds, humans are able to move efficiently between people. They look ahead to know which path would reduce the complexity of their interactions with others. Current navigation systems for virtual agents consider long‐term planning to find a path in the static environment and short‐term reactions to avoid collisions with close obstacles. Recently some mid‐term considerations have been added to avoid high density areas. However, there is no mid‐term planning among static and dynamic obstacles that would enable the agent to look ahead and avoid difficult paths or find easy ones as humans do. In this paper, we present a system for such mid‐term planning.Item Efficient and Reliable Self‐Collision Culling Using Unprojected Normal Cones(© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Wang, Tongtong; Liu, Zhihua; Tang, Min; Tong, Ruofeng; Manocha, Dinesh; Chen, Min and Zhang, Hao (Richard)We present an efficient and accurate algorithm for self‐collision detection in deformable models. Our approach can perform discrete and continuous collision queries on triangulated meshes. We present a simple and linear time algorithm to perform the normal cone test using the unprojected 3D vertices, which reduces to a sequence point‐plane classification tests. Moreover, we present a hierarchical traversal scheme that can significantly reduce the number of normal cone tests and the memory overhead using front‐based normal cone culling. The overall algorithm can reliably detect all (self) collisions in models composed of hundreds of thousands of triangles. We observe considerable performance improvement over prior continuous collision detection algorithms.We present an efficient and accurate algorithm for self‐collision detection in deformable models. Our approach can perform discrete and continuous collision queries on triangulated meshes. We present a simple and linear time algorithm to perform the normal cone test using the unprojected 3D vertices, which reduces to a sequence point‐plane classification tests. Moreover, we present a hierarchical traversal scheme that can significantly reduce the number of normal cone tests and the memory overhead using front‐based normal cone culling. The overall algorithm can reliably detect all (self) collisions in models composed of hundreds of thousands of triangles. We observe considerable performance improvement over prior continuous collision detection algorithms.Item Multi‐Variate Gaussian‐Based Inverse Kinematics(© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Huang, Jing; Wang, Qi; Fratarcangeli, Marco; Yan, Ke; Pelachaud, Catherine; Chen, Min and Zhang, Hao (Richard)Inverse kinematics (IK) equations are usually solved through approximated linearizations or heuristics. These methods lead to character animations that are unnatural looking or unstable because they do not consider both the motion coherence and limits of human joints. In this paper, we present a method based on the formulation of multi‐variate Gaussian distribution models (MGDMs), which precisely specify the soft joint constraints of a kinematic skeleton. Each distribution model is described by a covariance matrix and a mean vector representing both the joint limits and the coherence of motion of different limbs. The MGDMs are automatically learned from the motion capture data in a fast and unsupervised process. When the character is animated or posed, a Gaussian process synthesizes a new MGDM for each different vector of target positions, and the corresponding objective function is solved with Jacobian‐based IK. This makes our method practical to use and easy to insert into pre‐existing animation pipelines. Compared with previous works, our method is more stable and more precise, while also satisfying the anatomical constraints of human limbs. Our method leads to natural and realistic results without sacrificing real‐time performance.Inverse kinematics (IK) equations are usually solved through approximated linearizations or heuristics. These methods lead to character animations that are unnatural looking or unstable because they do not consider both the motion coherence and limits of human joints. In this paper, we present a method based on the formulation of multi‐variate Gaussian distribution models (MGDMs), which precisely specify the soft joint constraints of a kinematic skeleton. Each distribution model is described by a covariance matrix and a mean vector representing both the joint limits and the coherence of motion of different limbs.