옷감의 빠른 자가충돌 처리를 하기 위한 GPU 최적화된 BVH와 R-Triangle 기법
GPU-Optimized BVH and R-Triangle Methods for Rapid Self-Intersection Handling in Fabrics
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
본 논문에서는 삼각형 메쉬 기반 옷감 시뮬레이션에서 계산이 큰 자기충돌(Self-collision) 처리를GPU 기반으로 가속화하는 방법을 소개한다. CUDA(Compute Unified Device Architecture) 기반 병렬 최적화를 위해, 본 논문에서는 1) GPU에서 BVH(Bounding Volume Hierarchy) 트리를 효율적으로 구축, 업데이트 및 순회하는 방법을 제안하고, 2) 삼각형 메쉬 기반에서는R-Triangle(Representative-Triangle) 기법을 GPU에서 최적화하여 프리미티브 충돌 검사를 최소화한다. 결과적으로, 제안된 방법은 GPU 환경에서 옷감 시뮬레이션의 자기충돌과 객체 충돌을 CPU기반 알고리즘에 비해 빠르고 효율적으로 처리할 수 있으며, 다양한 장면에서 실험한 결과 5배~10 배정도 빠른 시뮬레이션 결과를 얻을 수 있다. 본 논문에서 제안하는 방법은 BVH를 GPU에서 최적화했기 때문에 BVH를 기반으로 활용하는 다양한 알고리즘과 분야에 쉽게 통합이 가능하다.
Abstract
In this paper, we present a GPU-based acceleration of computationally intensive self-collision processing in triangular mesh-based cloth simulation. For Compute Unified Device Architecture (CUDA)-based parallel optimization, we propose 1) an efficient way to build, update, and traverse the Bounding Volume Hierarchy (BVH) tree on the GPU, and 2) optimize the Representative-Triangle (R-Triangle) technique on the GPU to minimize primitive collision checking in triangular mesh-based cloth simulations. As a result, the proposed method can handle self-collisions and object collisions of cloth simulation in GPU environment faster and more efficiently than CPU-based algorithms, and experiments on various scenes show that it can achieve simulation results that are 5x to 10x faster. Since the proposed method is optimized for BVH on GPU, it can be easily integrated into various algorithms and fields that utilize BVH.
참고문헌 (22)
- Bridson, Robert, "Robust treatment of collisions, contact and friction for cloth animation", Proceedings of the 29th annual conference on Computer graphics and interactive techniques, pp.594~603 (2002)
- Tang, Min, "PSCC : Parallel self-collision culling with spatial hashing on GPUs", Proceedings of the ACM on Computer Graphics and Interactive Techniques, 1(1), pp.1~18 (2018)
- Dionisio, John David N., "3D virtual worlds and the metaverse : Current status and future possibilities", ACM Computing Surveys(CSUR), 45(3), pp.1~38 (2013)[DOI]
- Shams, Mahmoud Y., "The Future of Metaverse in the Virtual Era and Physical World", pp.27~42 (2023), Springer International Publishing
- Tang, Min, "CAMA: Contact‐aware matrix assembly with unified collision handling for GPU‐based cloth simulation", Computer Graphics Forum, 35(2), pp.511~521 (2016)[DOI]
- Jiang, Chenfanfu, "Anisotropic elastoplasticity for cloth, knit and hair frictional contact", ACM Transactions on Graphics (TOG), 36(4), pp.1~14 (2017)[DOI]
- Heo, Jae-Pil, "FASTCD: Fracturing-aware stable collision detection", ACM SIGGRAPH 2010 Posters, pp.1~1 (2010)
- Zhang, Xinyu, "Scalable collision detection using p-partition fronts on many-core processors", IEEE Transactions on Visualization and Computer Graphics, 20(3), pp.447~456 (2013)[DOI]
- Fan, Wenshan, "A hierarchical grid based framework for fast collision detection", Computer Graphics Forum, 30(5), pp.1451~1459 (2011), Blackwell Publishing Ltd[DOI]
- Weller, René, "kDet:Parallel constant time collision detection for polygonal objects", Computer Graphics Forum, 36(2), pp.131~141 (2017)[DOI]
- Tang, Min, "MCCD : Multi-core collision detection between deformable models using front-based decomposition", Graphical Models, 72(2), pp.7~23 (2010)[DOI]
- Tang, Min, "Interactive continuous collision detection between deformable models using connectivity-based culling", Proceedings of the 2008 ACM symposium on Solid and physical modeling, pp.25~36 (2008)
- Schvartzman, Sara C., "Star-contours for efficient hierarchical self-collision detection", ACM SIGGRAPH 2010 papers, pp.1~8 (2010)
- Wang, Tongtong, "Efficient and Reliable Self‐Collision Culling Using Unprojected Normal Cones", Computer Graphics Forum, 36(8), pp.487~498 (2017)[DOI]
- Lefebvre, Sylvain, "Perfect spatial hashing", ACM Transactions on Graphics (TOG), 25(3), pp.579~588 (2006)[DOI]
- Pabst, Simon, "Fast and scalable cpu", gpu collision detection for rigid and deformable surfaces, 2010, pp.29(5), 1605~1612[DOI]
- Faure, Xavier, "An Implicit Tensor-Mass solver on the GPU for soft bodies simulation", Eurographics Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS) (2012)
- Wong, Tsz Ho, "An adaptive octree grid for GPU-based collision detection of deformable objects", The Visual Computer, 30(6), pp.729~738 (2014)[DOI]
- Selle, Andrew, "Robust high-resolution cloth using parallelism, history-based collisions, and accurate friction", IEEE Transactions on Visualization and Computer Graphics, 15(2), pp.339~350 (2008)[DOI]
- Tang, Min, "CAMA: Contact‐aware matrix assembly with unified collision handling for GPU‐based cloth simulation", Computer Graphics Forum, 35(2), pp.511~521 (2016)[DOI]
- Popov, Stefan, "Stackless KD‐tree traversal for high performance GPU ray tracing", Computer Graphics Forum, 26(3), pp.415~424 (2007)[DOI]
- Curtis, Sean, "Fast collision detection for deformable models using representative-triangles", Proceedings of the 2008 symposium on Interactive 3D graphics and games, pp.61~69 (2008)