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PublicouEstela Reveles Alterado mais de 9 anos atrás
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Some techniques to Speed up Collision Detection Yalmar Ponce Atencio LCG/PESC/COPPE
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Problem Given a large environment with moving objects, Detect overlapping objects Overlapping triangles in each pair
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Goal Interactive collision detection between complex objects Large number of objects High primitive count Non-convex objects Open and closed objects Deformable objects Changing topology
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Related Work Collision detection Hardware accelerated techniques Object space techniques Two phases Broad phase – Compute object pairs in close proximity Narrow phase – Check each pair for exact collision detection
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Related Work Broad phase Spatial partitioning Sweep-and-prune Narrow phase Spatial partitioning Bounding volume hierarchies Surveys [ Klosowski 1998, Lin and Manocha 2003, Redon et al. 2002, Andrew Nealen et al. 2005 ]
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Limitations of Object-space Techniques Considerable pre-processing Hard to achieve real-time performance on complex deformable models
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Collision Detection using Graphics Hardware Primitive rasterization – sorting in screen-space Interference tests NV_OCCLUSION_QUERY Requires high screen resolution
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Image Space Techniques Use of graphics hardware CSG rendering [Goldfeather et al. 1989, Rossignac et al. 1990] Interferences and cross-sections [Baciu et al. 1998, Myszkowski 1995, Rossignac et al. 1992, Shinya and Forgue 1991] Virtual Surgery [Lombardo et al. 1999] Minkowski sums [Kim et al. 2001] Cloth animation [Vassilev et al. 2001] Proximity computation [Hoff et al. 2001, 2002] CULLIDE, R-CULLIDE, Q-CULLIDE[Govindaraju et al. 2003-2005]
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Limitations of Current Approaches Closed models Frame buffer readbacks – slow
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Outline Overview Pruning Algorithm HashedOctree Implementation and Results Conclusions and Future Work
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Outline Overview Pruning Techniques HashedOctree Implementation and Results Conclusions and Future Work
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Overview Potentially Colliding Set (PCS) computation Exact collision tests on the PCS using a HashedOctree
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Technique Object Level Pruning Sub-object Level Pruning Exact Tests GPU based PCS computation Using CPU
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Potentially Colliding Set (PCS) PCS Scene
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Outline Overview Pruning Techniques HashedOctree Implementation and Results Conclusions and Future Work
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Pruning Techniques Occlusion queries Back-face culling Convex models View volume culling glSelectBuffer()
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO View volume culling Using AABBs
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO A B Improvements Using OBBs Transform B for A orientation Use OBB B as cliping planes PCS B
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Outline Overview Pruning Techniques HashedOctree Implementation and Results Conclusions and Future Work
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Creation Hierarchical Recursively Hash [N.A.Gumerov et al. 2003] From hierarchical Octree or Using a generated Key Key is generated from parent nodes Hash table uses k mod 2 b ( b last bits) Octree x HashedOctree 1 101 110100 111 11000 11100 10111 10100 11101 11110 10101 10110 11001 11010 1111 11011
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Search in Octree p Hierarchical recursive
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Search in HashedOctree p Direct access Using key node
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Outline Overview Pruning Techniques HashedOctree Implementation and Results Conclusions and Future Work
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO HashedOctree Morton key Generated recursively Key is computed using Interleaving k (n) = x l y l z l x l-1 y l-1 z l-1 …x 1 y 1 z 1 l is the level of the octree Interleaving is achieved by “OR”ing
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO B A Potentially Colliding Set x HashedOctree Each object have a HashedOctree PCS B = trgls_in( OBB A OBB B ) Exact test PCS B x HashedOctree A
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Algorithm CS A = CS B = foreach (t B in PCS B ){ PCS A = foreach (p in t B ) PCS A HashedOctree A.searchElems(p) if (PCS A ) foreach (t A in PCS A ) if (t A t B ){ CS A t A CS B t B }
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Results Tests on a Pentium M 2.0Ghz with ATI X600 128Mb PCIe and 1Gb RAM Hierarchical Octree Depth Level 10 Hashed Octree Depth Level 10 Search a Point Cow 4315 Triangles 8626 Faces 9-11 us 4-4.5 us Dragon 48581 Triangles 93286 Faces 14-19 us 4-4.9 us Exact intersection Triangle-Triangle Torus x Torus 632 Triangles 1264 Faces 12-120 us 5-39 us Cow x Torus 45-390 us 15-99 us
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Outline Overview Pruning Techniques HashedOctree Implementation and Results Conclusions and Future Work
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Conclusions and Future Work Conclusions Earlier image based collision detection approaches present some limitations (Screen Resolution). Object level Pruning and Sub-object pruning are required. Hashed Octree reduces a query up to 80% over hierarchical Octree. Future Work Geometric models can be mapped efficiently on images (Geometry Images). Geometry images allow to generate Octrees and volume hierarchies in real-time on current GPUs.
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO Thanks all folks!
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UNIVERSIDADE FEDERAL DO RIO DE JANEIRO
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