“Evaluating the visual fidelity of physically based animations” by O’Sullivan, Dingliana, Giang and Kaiser

  • ©Carol O'Sullivan, John Dingliana, Thanh Giang, and Mary Kaiser

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Title:

    Evaluating the visual fidelity of physically based animations

Presenter(s)/Author(s):



Abstract:


    For many systems that produce physically based animations, plausibility rather than accuracy is acceptable. We consider the problem of evaluating the visual quality of animations in which physical parameters have been distorted or degraded, either unavoidably due to real-time frame-rate requirements, or intentionally for aesthetic reasons. To date, no generic means of evaluating or predicting the fidelity, either physical or visual, of the dynamic events occurring in an animation exists. As a first step towards providing such a metric, we present a set of psychophysical experiments that established some thresholds for human sensitivity to dynamic anomalies, including angular, momentum and spatio-temporal distortions applied to simple animations depicting the elastic collision of two rigid objects. In addition to finding significant acceptance thresholds for these distortions under varying conditions, we identified some interesting biases that indicate non-symmetric responses to these distortions (e.g., expansion of the angle between post-collision trajectories was preferred to contraction and increases in velocity were preferred to decreases). Based on these results, we derived a set of probability functions that can be used to evaluate the visual fidelity of a physically based simulation. To illustrate how our results could be used, two simple case studies of simulation levels of detail and constrained dynamics are presented.

References:


    1. BARRAZA, J. F., AND GRZYWACZ, N. M. 2002. Measurement of angular velocity in the perception of rotation. Vision Research 42, 2457–2462.Google ScholarCross Ref
    2. BARZEL, R., AND BARR, A. H. 1988. A modelling system based on dynamic constraints. In Computer Graphics (Proceedings of ACM SIGGRAPH 88), ACM, 179–188. Google Scholar
    3. BARZEL, R., HUGHES, J. F., AND WOOD, D. N. 1996. Plausible motion simulation for computer graphics animation. In Computer Animation and Simulation 96, 184–197. Google ScholarDigital Library
    4. BROGAN, D. C., AND HODGINS, J. K. 2002. Simulation level of detail for multiagent control. In Proceedings of the first international joint conference on Autonomous agents and multiagent systems, 199–206. Google Scholar
    5. CARLSON, D., AND HODGINS, J. 1997. Simulation levels of detail for real-time animation. In Proceedings Graphics Interface, 1–8. Google Scholar
    6. CARLTON, E. H., AND SHEPARD, R. N. 1990. Psychologically simple motions as geodesic paths: I. asymmetric objects. Journal of Mathematical Psychology 34, 127–188. Google ScholarDigital Library
    7. CHENNEY, S., AND FORSYTH, D. 1997. View-dependent culling of dynamic systems in virtual environments. In Proceedings of the ACM Symposium on Interactive 3D Graphics, 55–58. Google Scholar
    8. CHENNEY, S., AND FORSYTH, D. 2000. Sampling plausible solutions to multi-body constraint problems. In Proceedings of ACM SIGGRAPH 2000, ACM Press / ACM SIGGRAPH, 219–228. Google ScholarDigital Library
    9. CHENNEY, S., ARIKAN, O., AND FORSYTH, D. 2001. Proxy simulations for efficient dynamics. In Proceedings of Eurographics 2001, Short Presentations.Google Scholar
    10. CLEMENT, J. 1982. Students’ preconceptions in introductory mechanics. American Journal of Physics 50, 1, 66–71.Google ScholarCross Ref
    11. CORNSWEET, T. 1962. The staircase method in psychophysics. American Journal of Psychology 75, 485–491.Google ScholarCross Ref
    12. DALY, S. 1993. The visible differences predictor: an algorithm for the assessment of image fidelity. In Digital images and human vision, 179–206. Google Scholar
    13. DINGLIANA, J., AND O’SULLIVAN, C. 2000. Graceful degradation of collision handling in physically based animation. Computer Graphics Forum (Eurographics 2000 Proceedings) 19, 3, 239–247.Google ScholarCross Ref
    14. EHMANN, S. A., AND LIN, M. C. 2001. Accurate and fast proximity queries between polyhedra using convex surface decomposition. Computer Graphics Forum (Eurographics 2001 Proceedings) 20, 3, C500–C510.Google Scholar
    15. FUNKHOUSER, T., AND SÉQUIN, C. 1993. Adaptive display algorithm for interactive frame rates during visualization of complex virtual environments. In Proceedings of ACM SIGGRAPH 1993, ACM Press / ACM SIGGRAPH, 247–254. Google ScholarCross Ref
    16. GILDEN, D., AND PROFFITT, D. 1989. Understanding collision dynamics. Journal of Experimental Psychology: Human Perception and Performance 15, 2, 372–383.Google ScholarCross Ref
    17. GOTTSCHALK, S., LIN, M., AND MANOCHA, D. 1996. Obb-tree: A hierarchical structure for rapid interference detection. In Proceedings of ACM SIGGRAPH 1996, ACM Press / ACM SIGGRAPH, 171–180. Google ScholarDigital Library
    18. GRAZIANO, M. S. A., ANDERSON, R. A., AND SNOWDEN, R. J. 1994. Tuning of mst neurons to spiral motions. J. Neuroscience 14, 1, 54–67.Google ScholarCross Ref
    19. GROSS, D. 1999. Report from the fidelity implementation study group. In Fall Simulation Interoperability Workshop Papers.Google Scholar
    20. HODGINS, J., O’BRIEN, J., AND TUMBLIN, J. 1998. Perception of human motion with different geomentric models. IEEE Transactions on Visualization and Computer Graphics. 4, 4, 307–316. Google ScholarDigital Library
    21. HUBBARD, P. 1995. Collision detection for interactive graphics applications. IEEE Transactions on Visualization and Computer Graphics. 1, 3, 218–230. Google ScholarDigital Library
    22. KAISER, M. K., AND PROFFITT, D. R. 1987. Observers’ sensitivity to dynamic anomalies in collisions. Perception and Psychophysics 42, 3, 275–280.Google ScholarCross Ref
    23. KLOSOWSKI, J., HELD, M., MITCHELL, J., SOWIZRAL, H., AND ZIKAN, K. 1998. Efficient collision detection using bounding volume hierarchies of k-dops. IEEE Transactions on Visualization and Computer Graphics 4, 1, 21–36. Google ScholarDigital Library
    24. LEVITT, H. 1971. Transformed up-down methods in psychoacoustics. Journal of the Acoustical Society of America 49, 467–477.Google ScholarCross Ref
    25. LONGRIDGE, T., BRKI-COHEN, J., GO, T. H., AND KENDRA, A. J. 2001. Simulator fidelity considerations for training and evaluation of today’s airline pilots. In Proceedings of the 11th International Symposium on Aviation Psychology, The Ohio State University Press.Google Scholar
    26. LUEBKE, D., AND HALLEN, B. 2001. Perceptually driven simplification for interactive rendering. In Rendering Techniques, Springer-Verlag, London, S. Gortler and K. Myszkowski, Eds., 223–234. Google Scholar
    27. MICHOTTE, A. 1963. The Perception of Causality. Basic Books, New York.Google Scholar
    28. MIRTICH, B. 2000. Timewarp rigid body simulation. In Proceedings of ACM SIGGRAPH 2000, ACM Press / ACM SIGGRAPH, 193–200. Google ScholarDigital Library
    29. MYSZKOWSKI, K., TAWARA, T., AKAMINE, H., AND SEIDEL, H.-P. 2001. Perception-guided global illumination solution for animation rendering. In Proceedings of ACM SIGGRAPH 2001, ACM Press / ACM SIGGRAPH, 221–230. Google ScholarDigital Library
    30. O’BRIEN, D., FISHER, S., AND LIN, M. C. 2001. Automatic simplification of particle system dynamics. In Proceedings of Computer Animation, 2001.Google ScholarCross Ref
    31. O’SULLIVAN,C., AND DINGLIANA, J. 2001. Collisions and perception. ACM Transactions on Graphics (TOG) 20, 3, 151–168. Google ScholarDigital Library
    32. POPOVIC, J., SEITZ, S. M., ERDMANN, M., POPOVIC, Z., AND WITKIN, A. 2000. Interactive manipulation of rigid body simulations. In Proceedings of ACM SIGGRAPH 2000, ACM Press / ACM SIGGRAPH, 209–217. Google ScholarDigital Library
    33. PROFFITT, D., AND GILDEN, D. 1989. Understanding natural dynamics. Journal of Experimental Psychology: Human Perception and Performance 15, 2, 384–393.Google ScholarCross Ref
    34. RAMASUBRAMANIAN, M., PATTANAIK, S. N., AND GREENBERG, D. P. 1999. A perceptually based physical error metric for realistic image synthesis. In Proceedings of ACM SIGGRAPH 1999, ACM Press / ACM SIGGRAPH, 73–82. Google ScholarDigital Library
    35. ROZA, M., VOOGD, J., JENSE, H., ANDVAN GOOL, P. 1999. Fidelity requirements specification: A process oriented view. In Fall Simulation Interoperability Workshop.Google Scholar
    36. ROZA, M., VAN GOOL, P., AND VOOGD, J. 2000. Fidelity considerations for civil aviation distributed simulations. In Proc. AIAA Modeling and Simulation Technologies Conference.Google ScholarCross Ref
    37. WANG, Z., BOVIK, A., AND LU, L. 2002. Why is image quality assessment so difficult? In Proceedings of the IEEE International Conference on Acoustics, Speech, & Signal Processing, vol. 4, 3313–3316.Google Scholar
    38. WATSON, B., FRIEDMAN, A., AND MCGAFFEY, A. 2001. Measuring and predicting visual fidelity. In Proceedings of ACM SIGGRAPH 2001, ACM Press / ACM SIGGRAPH, 213–220. Google ScholarDigital Library
    39. YEE, H., PATTANAIK, S., AND GREENBERG, D. P. 2001. Spatiotemporal sensitivity and visual attention for efficient rendering of dynamic environments. ACM Transactions on Graphics 19, 2, 39–65. Google ScholarDigital Library


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