Collision Detection for Moving Polyhedra
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kinetic collision detection for simple polygons
Proceedings of the sixteenth annual symposium on Computational geometry
Robust treatment of collisions, contact and friction for cloth animation
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Normal bounds for subdivision-surface interference detection
Proceedings of the conference on Visualization '01
Fast Collision Detection Among Multiple Moving Spheres
IEEE Transactions on Visualization and Computer Graphics
Collision prediction for polyhedra under screw motions
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Impulse-based dynamic simulation of rigid body systems
Impulse-based dynamic simulation of rigid body systems
Real-Time subspace integration for St. Venant-Kirchhoff deformable models
ACM SIGGRAPH 2005 Papers
Interactive collision detection between deformable models using chromatic decomposition
ACM SIGGRAPH 2005 Papers
Model reduction for real-time fluids
ACM SIGGRAPH 2006 Papers
Fast proximity computation among deformable models using discrete Voronoi diagrams
ACM SIGGRAPH 2006 Papers
Interactive continuous collision detection for non-convex polyhedra
The Visual Computer: International Journal of Computer Graphics
Continuous collision detection for articulated models using Taylor models and temporal culling
ACM SIGGRAPH 2007 papers
Fast collision detection for deformable models using representative-triangles
Proceedings of the 2008 symposium on Interactive 3D graphics and games
Deformable object animation using reduced optimal control
ACM SIGGRAPH 2009 papers
IEEE Transactions on Visualization and Computer Graphics
Bounded normal trees for reduced deformations of triangulated surfaces
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Multi-core collision detection between deformable models
2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling
C2A: controlled conservative advancement for continuous collision detection of polygonal models
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Fast continuous collision detection using deforming non-penetration filters
Proceedings of the 2010 ACM SIGGRAPH symposium on Interactive 3D Graphics and Games
Star-contours for efficient hierarchical self-collision detection
ACM SIGGRAPH 2010 papers
Subspace self-collision culling
ACM SIGGRAPH 2010 papers
Accelerating physics in large, continuous virtual environments
Concurrency and Computation: Practice & Experience
Fast continuous collision culling with deforming noncollinear filters
Computer Animation and Virtual Worlds
Radial view based culling for continuous self-collision detection of skeletal models
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Dynamic radial view based culling for continuous self-collision detection
Proceedings of the 18th meeting of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
Hi-index | 0.00 |
In this paper, we present a novel fast Continuous Collision Detection (CCD) method using SIMD capacity of CPU and idea of dimension reduction. We apply a parallel linear filter culling performed in one-dimensional subspace followed by a parallel planar filter culling performed in two-dimensional subspace before each elementary test, which simultaneously and conservatively tests the relative motion of each primitive pairs in various selected subspace. CPU's SIMD capacity is utilized for parallelizing the projection and filtering process in each subspace. Parallel filter culling in subspace removes a large amount of redundant elementary tests with low cost, and improves the overall performance of collision query. We demonstrate the advantages of our approach when comparing with previous alternatives in various dynamic scenes as benchmarks. In experiments, we observe up to 99% removal of false positives, and a huge magnitude of speed improvement on elementary tests (over 3x). Since our method only correlates the elementary test, it is scalable and can be easily integrated with various available single or multicore CPU based CCD algorithm. In addition, the performance of our method is less sensitive to varying step time.