Advertisement

A Model of Collision Perception for Real-Time Animation

  • Carol O’Sullivan
  • Ralph Radach
  • Steven Collins
Part of the Eurographics book series (EUROGRAPH)

Abstract

A model of human visual perception of collisions is presented, based on two-dimensional measures of eccentricity and separation. The model is validated by performing psychophysical experiments. We demonstrate the feasibility of using this model as the basis for perceptual scheduling of interruptible collision detection in a real-time animation of large numbers of visually homogeneous objects. The user’s point of fixation may be either tracked or estimated. By using a priority queue scheduling algorithm, perceived collision inaccuracy was approximately halved. The ideas presented are applicable to other tasks where the processing of fine detail leads to a computational bottleneck.

Keywords

Collision Detection Perceptual Grouping Psychophysical Experiment Human Visual Perception Sequential Schedule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Albright, T.D. Centrifugal directional bias in the middle temporal visual area (MT) of the macaque. Vis. Neurosci. 2(17), 7–188. 1989.Google Scholar
  2. 2.
    Aubert, H. Foerster, O. Beiträge zur Kentniss des indirekten Sehens. Arch. Ophth 3, 1–37 1857.Google Scholar
  3. 3.
    Barzel, R. Hughes, J.F. Wood, D.N. Plausible Motion Simulation for Computer Graphics Animation. Computer Animation and Simulation ’96. 183–197. 1996Google Scholar
  4. 4.
    Chung, S.T.L. Levi, D.M. Bedell, H.E. Vernier in Motion: What Accounts for the Threshold Elevation? Vision Research, 36(16) 2395–2410. 1996CrossRefGoogle Scholar
  5. 5.
    Cohen, J.D. Lin, M.C. Manocha, D. Ponamgi, M.K. I-COLLIDE: An Interactive and Exact Collision Detection System for Large-Scaled Environments. ACM Int. 3D Graphics Conference. 189–196. 1995.Google Scholar
  6. 6.
    Deering, M. High Resolution Virtual Reality. Computer Graphics, 26, 2, 195–202. 1992.CrossRefGoogle Scholar
  7. 7.
    DeValois, R.L, and De Valois, K.K. Spatial Vision. New York: Oxford University. 1988.Google Scholar
  8. 8.
    Ferwerda, J.A. Pattanaik, S.N. Shirley, P. Greenberg, D.P. A Model of Visual Adaptation for Realistic Image Synthesis. SIGGRAPH ’96. 249–258. 1996Google Scholar
  9. 9.
    Ferwerda, J.A. Pattanaik, S.N. Shirley, P. Greenberg, D.P. A Model of Visual Masking for Computer Graphics. SIGGRAPH ’97. 143–152. 1997.Google Scholar
  10. 10.
    Funkhouser,T.A. Sequin, C.H. Adaptive Display Algorithm for Interactive Frame Rates During Visualization of Complex Virtual Environments. SIGGRAPH ’93 247–254. 1993.Google Scholar
  11. 11.
    Gottschalk, S. Lin, M.C. Manocha, D. OBB-Tree: A Hierarchical Structure for Rapid Interference Detection. SIGGRAPH. 1996Google Scholar
  12. 12.
    Graziano, M.S.A. Anderson, R.A., Snowden, R.J. Tuning of MST Neurons to Spiral Motions. Journal of Neuroscience, 14(1): 54–67. 1994Google Scholar
  13. 13.
    Greenberg et al. A Framework for Realistic Image Synthesis. SIGGRAPH. 477–494. 1997.Google Scholar
  14. 14.
    Hubbard, P.M. Collision Detection for Interactive Graphics Applications. IEEE Transactions on Visualization and Computer Graphics. 1(3) 218–230. 1995.CrossRefGoogle Scholar
  15. 15.
    Hubel, D.H. Wiesel, T.N. Receptive fields and functional architecture of monkey striate cortex. J.Physiology, 195,215–243, 1968Google Scholar
  16. 16.
    Jacob, R.J.K. Eye Tracking in Advanced Interface Design. In Barfield,W. and Furness, T.A. (Eds) Virtual Environments and Advanced Interface Design. 258–288. 1995Google Scholar
  17. 17.
    Klosowski, J.T. Held, M. Mitchell, J.S.B. Sowizral, H. Zikan, K. Efficient Collision Detection Using Bounding Volume Hierarchies of k-DOPs. IEEE Tr. Vis. & Comp. Graph. 4(1). 1998.Google Scholar
  18. 18.
    Mahoney, J.V. Ullman, S. Image chunking defining spatial building blocks for scene analysis. Z. Pylyshyn (Ed.) Computational processes in human vision. 1988.Google Scholar
  19. 19.
    Nies, U. Bedenk, B., Heller, D. & Radach, R.. Eye movement patterns during search in a homogeneous background. Becker, Deubel, Mergner (Eds). Current Oculomotor Res. 1998.Google Scholar
  20. 20.
    O’Sullivan, C.A. Dingliana, J. Real-Time Collision Detection and Response using Sphere-Trees. Proc. Spring Conference on Computer Graphics, Slovakia. 83–92. 1999.Google Scholar
  21. 21.
    Palmer, I.J. Grimsdale, R.L. Collision Detection for Animation using Sphere-Trees. Computer Graphics Forum, 14(2) 105–116. 1995.CrossRefGoogle Scholar
  22. 22.
    Quinlan, S. Efficient Distance Computation between Non-Convex Object. Proceedings International Conference on Robotics and Automation. 3324–3329. 1994.Google Scholar
  23. 23.
    Saarinen,J. Visual search for global and local stimulus features. Perception 23, 237–243. 1994.CrossRefGoogle Scholar
  24. 24.
    Schiff, W. Detwiler, M. Information used in judging impending collision. Perception 8, 647–658. 1994.CrossRefGoogle Scholar
  25. 25.
    Skerjanc, R. and Pastoor, S. New generation of 3-D desktop computer interfaces, SPIE: The Engineering Reality of Virtual Reality, 439 – 447, 1997.Google Scholar
  26. 26.
    Tootell, R.B.H, Silverman, M.S. Switkes, E, De Valois, R.L. Deoxyglucose analysis of retinotopic organization in primate striate cortex. Science, 218, 902–904. 1982.CrossRefGoogle Scholar
  27. 27.
    Treisman, A. Perceptual Grouping and Attention in Visual Search for Features and for Objects. J. Experimental Psychology: Human Perception and Performance 8, 194–214. 1982.CrossRefGoogle Scholar
  28. 28.
    Weymouth, R.W. Visual sensory units and the minimal angle of resolution. American Journal of Ophthamology, 46, 102–113. 1958.Google Scholar
  29. 29.
    Yap, Y.L. Levi, D.M. Klein, S.A. Peripheral hyperacuity: isoeccentric bisection is better than radial bisection. J. Opt. Soc. Am. A, 4(8), 1562–1567. 1987.CrossRefGoogle Scholar
  30. 30.
    Zeki, S.M. Functional Organization of a Visual Area in the Posterior Bank of the Superior Temporal Sulcus of the Rhesus Monkey. J. Physiology. 236, 549–573. 1974.Google Scholar

Copyright information

© Spinger-Verlag/Wien 1999

Authors and Affiliations

  • Carol O’Sullivan
    • 1
  • Ralph Radach
    • 2
  • Steven Collins
    • 1
  1. 1.Computer Science Department, Trinity College DublinImage Synthesis GroupIreland
  2. 2.Institute of PsychologyTechnical University of AachenAachenGermany

Personalised recommendations