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Fast collision detection using the A-buffer

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Abstract

This paper presents a novel and fast image-space collision detection algorithm with the A-buffer, where the GPU computes the potentially colliding sets (PCSs), and the CPU performs the standard triangle intersection test. When the bounding boxes of two objects intersect, the intersection is passed to the GPU. The object surfaces in the intersection are rendered into the A-buffer. Rendering into the A-buffer is up to eight-times faster than the ordinary approaches. Then, PCSs are computed by comparing the depth values of each texel of the A-buffer. A PCS consists of only two triangles. The PCSs are read back to the CPU, and the CPU computes the intersection points between the triangles. The proposed algorithm runs extremely fast, does not require any preprocessing, can handle dynamic objects including deformable and fracturing models, and can compute self-collisions. Such versatility and performance gain of the proposed algorithm prove its usefulness in real-time applications such as 3D games.

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References

  1. Baciu, G., Wong, S.K., Sun, H.: RECODE: An image-based collision detection algorithm. J. Vis. Comput. Animation 10(4), 181–192 (1999)

    Article  Google Scholar 

  2. Bavoil, L., Callahan, S.P., Lefohn, A., Comba, J.L.D., Silva, C.T.: Multi-fragment effects on the gpu using the k-buffer. In: I3D ’07: Proceedings of the 2007 Symposium on Interactive 3D Graphics and Games, pp. 97–104. ACM, New York, NY (2007)

    Chapter  Google Scholar 

  3. Blythe, D.: The direct3d 10 system. ACM Trans. Graph. 25(3), 724–734 (2006)

    Article  MathSciNet  Google Scholar 

  4. Gottschalk, S., Lin, M.C., Manocha, D.: OBBTree: A hierarchical structure for rapid interference detection. Computer Graphics (SIGGRAPH ’96 Proceedings) 30, 171–180 (1996)

    Google Scholar 

  5. Govindaraju, N.K., Knott, D., Jain, N., Kabul, I., Tamstorf, R., Gayle, R., Lin, M.C., Manocha, D.: Interactive collision detection between deformable models using chromatic decomposition. ACM Trans. Graph. 24(3), 991–999 (2005)

    Article  Google Scholar 

  6. Govindaraju, N.K., Lin, M.C., Manocha, D.: Fast and reliable collision culling using graphics hardware. In: VRST ’04: Proc. of ACM Symposium on Virtual Reality Software and Technology, pp. 2–9. ACM, New York, NY (2004)

    Chapter  Google Scholar 

  7. Govindaraju, N.K., Lin, M.C., Manocha, D.: Quick-CULLIDE: Fast inter- and intra-object collision culling using graphics hardware. In: VR ’05: Proc. of IEEE Virtual Reality 2005, pp. 59–66. IEEE Computer Society, Washington, DC (2005)

    Chapter  Google Scholar 

  8. Govindaraju, N.K., Redon, S., Lin, M.C., Manocha, D.: CULLIDE: Interactive collision detection between complex models in large environments using graphics hardware. In: HWWS ’03: Proc. of ACM SIGGRAPH/Eurographics Conference on Graphics Hardware, pp. 25–32. Eurographics Association, Aire-la-Ville, Switzerland (2003)

    Google Scholar 

  9. Grand, S.L.: Broad-phase collision detection with CUDA. In: Nguyen, H. (ed.) GPU Gems 3, chap. 32, pp. 697–722. Addison-Wesley (2007)

  10. Harris, M., Sengupta, S., Owens, J.D.: Parallel prefix sum (scan) with CUDA. In: Nguyen, H. (ed.) GPU Gems 3, chap. 39, pp. 851–876. Addison-Wesley (2007)

  11. He, T.: Fast collision detection using QuOSPO trees. In: I3D ’99: Proc. of the 1999 Symposium on Interactive 3D Graphics, pp. 55–62. ACM, New York, NY (1999)

    Chapter  Google Scholar 

  12. Heidelberger, B., Teschner, M., Gross, M.: Realtime volumetric intersections of deforming objects. In: Ertl, T. (ed.) VMV ’03: Proc. of the 2003 Vision, Modeling, and Visualization Conference, pp. 461–468. Aka GmbH, München (2003)

    Google Scholar 

  13. Heidelberger, B., Teschner, M., Gross, M.: Detection of collisions and self-collisions using image-space techniques. J. Winter School Comput. Graph. 12(3), 145–152 (2004)

    Google Scholar 

  14. Hoff, K.E., Zaferakis, A., Lin, M.C., Manocha, D.: Fast 3D geometric proximity queries between rigid and deformable models using graphics hardware acceleration. Tech. Rep. TR02–004, Department of Computer Science, University of North Carolina (2002)

  15. Horn, D.: Stream reduction operations for gpgpu applications. In: Pharr, M. (ed.) GPU Gems 2, chap. 36, pp. 573–589. Addison-Wesley (2005)

  16. Hubbard, P.M.: Interactive collision detection. In: Proc. of IEEE Symposium on Research Frontiers in Virtual Reality 1993, pp. 24–32. IEEE Computer Society, San Jose, CA (1993)

    Chapter  Google Scholar 

  17. Jang, H., Jeong, T., Han, J.: Image-space collision detection through alternate surface peeling. In: ISVC ’07: Proc. of International Symposium on Visual Computing. Lect. Note Comput. Sci., vol. 4841, pp. 66–75. Springer (2007)

  18. Klosowski, J.T., Held, M., Mitchell, J.S.B., Sowizral, H., Zikan, K.: Efficient collision detection using bounding volume hierarchies of k-DOPs. IEEE Trans. Vis. Comput. Graph. 4(1), 21–36 (1998)

    Article  Google Scholar 

  19. Liu, B., Wei, L.Y., Xu, Y.Q.: Multi-layer depth peeling via fragment sort. Tech. Rep. MSR-TR-2006-81, Microsoft Research Asia (2006)

  20. Mezger, J., Kimmerle, S., Etzmuss, O.: Hierarchical techniques in collision detection for cloth animation. J. Winter School Comput. Graph. 11(2), 322–329 (2003)

    Google Scholar 

  21. Myers, K., Bavoil, L.: Stencil routed A-buffer. In: SIGGRAPH ’07: ACM SIGGRAPH 2007 Sketches, p. 21. ACM, New York, NY (2007)

    Google Scholar 

  22. Myszkowski, K., Okunev, O.G., Kunii, T.L.: Fast collision detection between computer solids using rasterizing graphics hardware. Visual Comput. 11(9), 497–511 (1995)

    Article  Google Scholar 

  23. Palmer, I., Grimsdale, R.: Collision detection for animation using sphere-trees. Comput. Graph. Forum 14(2), 105–116 (1995)

    Article  Google Scholar 

  24. Shinya, M., Forgue, M.: Interference detection through rasterization. J. Vis. Comput. Animation 2(4), 131–134 (1991)

    Article  Google Scholar 

  25. Teschner, M., Heidelberger, B., Mueller, M., Pomeranets, D., Gross, M.: Optimized spatial hashing for collision detection of deformable objects. In: Ertl, T. (ed.) VMV ’03: Proc. of the 2003 Vision, Modeling, and Visualization Conference, pp. 47–54. München (2003)

  26. Van den Bergen, G.: Efficient collision detection of complex deformable models using aabb trees. J. Graph. Tools 2(4), 1–13 (1997)

    MATH  Google Scholar 

  27. Vassilev, T., Spanlang, B., Chrysanthou, Y.: Fast cloth animation on walking avatars. Comput. Graph. Forum 20(3), 260–267 (2001)

    Article  Google Scholar 

  28. Zachmann, G., Felger, W.: The boxtree: Enabling realtime and exact collision detection of arbitrary polyhedra. In: Proc. of Workshop on Simulation and Interaction in Virtual Environments 1995, pp. 104–113 (1995)

  29. Zhang, X., Kim, Y.: Interactive collision detection for deformable models using streaming aabbs. IEEE Trans. Vis. Comput. Graph. 13(2), 318–329 (2007)

    Article  Google Scholar 

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  1. Game Research Center, Korea University, Seoul, Korea

    Hanyoung Jang & JungHyun Han

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  1. Hanyoung Jang
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  2. JungHyun Han
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Correspondence to JungHyun Han.

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Jang, H., Han, J. Fast collision detection using the A-buffer. Visual Comput 24, 659–667 (2008). https://doi.org/10.1007/s00371-008-0246-8

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  • DOI: https://doi.org/10.1007/s00371-008-0246-8

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