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Fast and reliable collision culling using graphics hardware

Published:10 November 2004Publication History

ABSTRACT

We present a reliable culling algorithm that enables fast and accurate collision detection between triangulated models in a complex environment. Our algorithm performs fast visibility queries on the GPUs for eliminating a subset of primitives that are not in close proximity. To overcome the accuracy problems caused by the limited viewport resolution, we compute the Minkowski sum of each primitive with a sphere and perform reliable 2.5D overlap tests between the primitives. We are able to achieve more effective collision culling as compared to prior object-space culling algorithms. We integrate our culling algorithm with CULLIDE [8] and use it to perform reliable GPU-based collision queries at interactive rates on all types of models, including non-manifold geometry, deformable models, and breaking objects.

References

  1. Tomas Akenine-Moller and Jacob Strom. Graphics for the masses: a hardware rasterization architecture for mobile phones. ACM Trans. Graph., 22(3):801--808, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. G. Baciu and S. K. Wong. Image-based techniques in a hybrid collision detector. IEEE Trans. on Visualization and Computer Graphics, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. Baciu, S. K. Wong, and H. Sun. Recode: An image-based collision detection algorithm. Proc. of Pacific Graphics, pages 497--512, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. G. Barequet, B. Chazelle, L. Guibas, J. Mitchell, and A. Tal. Boxtree: A hierarchical representation of surfaces in 3D. In Proc. of Eurographics'96, 1996.Google ScholarGoogle ScholarCross RefCross Ref
  5. N. Beckmann, H. Kriegel, R. Schneider, and B. Seeger. The r*-tree: An efficient and robust access method for points and rectangles. Proc. SIGMOD Conf. on Management of Data, pages 322--331, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. J. Cohen, M. Lin, D. Manocha, and M. Ponamgi. I-COLLIDE: An interactive and exact collision detection system for large-scale environments. In Proc. of ACM Interactive 3D Graphics Conference, pages 189--196, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. S. Gottschalk, M. Lin, and D. Manocha. OBB-Tree: A hierarchical structure for rapid interference detection. Proc. of ACM Siggraph'96, pages 171--180, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. N. Govindaraju, S. Redon, M. Lin, and D. Manocha. CULLIDE: Interactive collision detection between complex models in large environments using graphics hardware. Proc. of ACM SIGGRAPH/Eurographics Workshop on Graphics Hardware, pages 25--32, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Alexander Gress and Gabriel Zachmann. Object-space interference detection on programmable graphics hardware. In SIAM Conf. on Geometric Design and Computing, Seattle, Washington, November13-17 2003.Google ScholarGoogle Scholar
  10. B. Heidelberger, M. Teschner, and M. Gross. Real-time volumetic intersections of deforming objects. Proc. of Vision, Modeling and Visualization, 2003.Google ScholarGoogle Scholar
  11. M. Held, J. Klosowski, and J. S. B. Mitchell. Real-time collision detection for motion simulation within complex environments. In Proc. ACM SIGGRAPH'96 Visual Proceedings, page 151, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. K. Hoff, A. Zaferakis, M. Lin, and D. Manocha. Fast and simple 2d geometric proximity queries using graphics hardware. Proc. of ACM Symposium on Interactive 3D Graphics, pages 145--148, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. P. M. Hubbard. Interactive collision detection. In Proceedings of IEEE Symposium on Research Frontiers in Virtual Reality, October 1993.Google ScholarGoogle ScholarCross RefCross Ref
  14. P. Jimenez, F. Thomas, and C. Torras. 3d collision detection: A survey. Computers and Graphics, 25(2):269--285, 2001.Google ScholarGoogle ScholarCross RefCross Ref
  15. B. Kelleher. Pixelvision architecture. Technical Report 1998--013, Digital Systems Research Center, 1998.Google ScholarGoogle Scholar
  16. Y. J. Kim, M. A. Otaduy, M. C. Lin, and D. Manocha. Fast penetration depth computation for physically-based animation. Proc. of ACM Symposium on Computer Animation, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. Klosowski, M. Held, J. S. B. Mitchell, H. Sowizral, and K. Zikan. Efficient collision detection using bounding volume hierarchies of k-dops. IEEE Trans. on Visualization and Computer Graphics, 4(1):21--37, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. D. Knott and D. Pai. Cinder: Collision and interference detection in real-time using graphics hardware. Proc. of Graphics Interface, pages 73--80, 2003.Google ScholarGoogle Scholar
  19. M. Lin and S. Gottschalk. Collision detection between geometric models: A survey. Proc. of IMA Conference on Mathematics of Surfaces, 1998.Google ScholarGoogle Scholar
  20. Joel McCormack and Robert McNamara. Tiled polygon traversal using half-plane edge functions. In Proceedings of the ACM SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware, pages 15--21. ACM Press, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. T. Moller. A fast triangle-triangle intersection test. Journal of Graphics Tools, 2(2), 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. S. Morein. ATI Radeon HyperZ technology. In ACM SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware, Hot3D Proceedings, 2000.Google ScholarGoogle Scholar
  23. K. Myszkowski, O. G. Okunev, and T. L. Kunii. Fast collision detection between complex solids using rasterizing graphics hardware. The Visual Computer, 11(9):497--512, 1995.Google ScholarGoogle ScholarCross RefCross Ref
  24. M. Lin N. Govindaraju and D. Manocha. Quick-cullide: Fast inter- and intra-object collision culling using graphics hardware. Technical report, University of North Carolina at Chapel Hill, July 2004.Google ScholarGoogle Scholar
  25. M. Ponamgi, D. Manocha, and M. Lin. Incremental algorithms for collision detection between solid models. IEEE Transactions on Visualization and Computer Graphics, 3(1):51--67, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. S. Quinlan. Efficient distance computation between non-convex objects. In Proceedings of International Conference on Robotics and Automation, pages 3324--3329, 1994.Google ScholarGoogle Scholar
  27. Ramesh Raskar and Michael Cohen. Image precision silhouette edges. In Proceedings of the 1999 symposium on Interactive 3D graphics, pages 135--140. ACM Press, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. J. Rossignac, A. Megahed, and B. D. Schneider. Interactive inspection of solids: cross-sections and interferences. In Proceedings of ACM Siggraph, pages 353--60, 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. M. Shinya and M. C. Forgue. Interference detection through rasterization. The Journal of Visualization and Computer Animation, 2(4):131--134, 1991.Google ScholarGoogle ScholarCross RefCross Ref
  30. Freesolid: Software library for interference detection. http://www.win.tue.nl/ gino/solid/.Google ScholarGoogle Scholar
  31. T. Vassilev, B. Spanlang, and Y. Chrysanthou. Fast cloth animation on walking avatars. Computer Graphics Forum (Proc. of Eurographics'01), 20(3):260--267, 2001.Google ScholarGoogle Scholar

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              cover image ACM Conferences
              VRST '04: Proceedings of the ACM symposium on Virtual reality software and technology
              November 2004
              226 pages
              ISBN:1581139071
              DOI:10.1145/1077534

              Copyright © 2004 ACM

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              Publication History

              • Published: 10 November 2004

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