“Push it real: perceiving causality in virtual interactions” by Hoyet, McDonnell and O’Sullivan

  • ©Ludovic Hoyet, Rachel McDonnell, and Carol O'Sullivan




    Push it real: perceiving causality in virtual interactions



    With recent advances in real-time graphics technology, more realistic, believable and appealing virtual characters are needed than ever before. Both player-controlled avatars and non-player characters are now starting to interact with the environment, other virtual humans and crowds. However, simulating physical contacts between characters and matching appropriate reactions to specific actions is a highly complex problem, and timing errors, force mismatches and angular distortions are common. To investigate the effect of such anomalies on the perceived realism of two-character interactions, we captured a motion corpus of pushing animations and corresponding reactions and then conducted a series of perceptual experiments. We found that participants could easily distinguish between five different interaction forces, even when only one of the characters was visible. Furthermore, they were sensitive to all three types of anomalous interactions: timing errors of over 150ms were acceptable less than 50% of the time, with early or late reactions being equally perceptible; participants could perceive force mismatches, though over-reactions were more acceptable than under-reactions; finally, angular distortions when a character reacts to a pushing force reduce the acceptability of the interactions, but there is some evidence for a preference of expansion away from the pushing character’s body. Our results provide insights to aid in designing motion capture sessions, motion editing strategies and balancing animation budgets.


    1. Arikan, O., Forsyth, D. A., and O’Brien, J. F. 2005. Pushing people around. In Proc. of SCA ’05, 59–66. Google ScholarDigital Library
    2. De Leva, P. 1996. Adjustments to zatsiorsky-seluyanov’s segment inertia parameters. Journal of Bomechanics 29, 1223–1230.Google ScholarCross Ref
    3. Ho, E. S. L., Komura, T., and Tai, C.-L. 2010. Spatial relationship preserving character motion adaptation. ACM Trans. Graph. 29, 4 (July), 33:1–33:8. Google ScholarDigital Library
    4. Hodgins, J., Jörg, S., O’Sullivan, C., Park, S. I., and Mahler, M. 2010. The saliency of anomalies in animated human characters. ACM Trans. Appl. Percept. 7, 4 (July), 22:1–22:14. Google ScholarDigital Library
    5. Hoyet, L., Multon, F., Lecuyer, A., and Komura, T. 2010. Can we distinguish biological motions of virtual humans?: perceptual study with captured motions of weight lifting. In Proc. of VRST’10, 87–90. Google ScholarDigital Library
    6. Kim, M., Hyun, K., Kim, J., and Lee, J. 2009. Synchronized multi-character motion editing. ACM Trans. Graph. 28, 3 (July), 79:1–79:9. Google ScholarDigital Library
    7. Komura, T., Ho, E. S. L., and Lau, R. W. H. 2005. Animating reactive motion using momentum-based inverse kinematics: Motion capture and retrieval. CAVW 16, 3-4, 213–223. Google ScholarDigital Library
    8. Kulpa, R., Multon, F., and Arnaldi, B. 2005. Morphology-independent representation of motions for interactive human-like animation. CGF, EG 2005 special issue 24, 3, 343–352.Google Scholar
    9. Kwon, T., Cho, Y.-S., Park, S. I., and Shin, S. Y. 2008. Two-character motion analysis and synthesis. IEEE Trans. on Visualization and Computer Graphics 14 (May), 707–720. Google ScholarDigital Library
    10. Laidacker, A., and Barbeau, N. 2011. Living crowds: Ai & animation in assassins creed: Brotherhood. Presented at Game Developers Conference, San Francisco, CA, Feb 28-Mar 4.Google Scholar
    11. Lee, K. H., Choi, M. G., and Lee, J. 2006. Motion patches: building blocks for virtual environments annotated with motion data. ACM Trans. Graph. 25, 3 (July), 898–906. Google ScholarDigital Library
    12. Liu, C. K., Hertzmann, A., and Popović, Z. 2006. Composition of complex optimal multi-character motions. In Proc. of SCA’06, 215–222. Google ScholarDigital Library
    13. Majkowska, A., and Faloutsos, P. 2007. Flipping with physics: motion editing for acrobatics. In Proc. of SCA ’07, 35–44. Google ScholarDigital Library
    14. McCann, J., and Pollard, N. 2007. Responsive characters from motion fragments. ACM Trans. Graph. 26, 3 (July). Google ScholarDigital Library
    15. Michaels, C. F., and de Vries, M. M. 1998. Higher order and lower order variables in the visual perception of relative pulling force. Journal of Experimental Psychology: Human Perception and Performance 24, 2, 526–546.Google ScholarCross Ref
    16. Michotte, A. 1963. The perception of causality. Basic Books, New York.Google Scholar
    17. O’Sullivan, C., Dingliana, J., Giang, T., and Kaiser, M. K. 2003. Evaluating the visual fidelity of physically based animations. ACM Trans. Graph. 22, 3, 527–536. Google ScholarDigital Library
    18. Reitsma, P., and O’Sullivan, C. 2009. Effect of scenario on perceptual sensitivity to errors in animation. ACM Trans. Appl. Percept. 6, 3, 1–16. Google ScholarDigital Library
    19. Reitsma, P., Andrews, J., and Pollard, N. 2008. Effect of character animacy and preparatory motion on perceptual magnitude of errors in ballistic motion. In Proc. of Eurographics ’08.Google Scholar
    20. Runeson, S., and Frykholm, G. 1983. Kinematic specification of dynamics as an informational basis for person-and-action perception: Expectation, gender recognition, and deceptive intention. Journal of Experimental Psychology: General 112, 4 (Dec.), 585–615.Google ScholarCross Ref
    21. Scholl, B., and Tremoulet, P. 2000. Perceptual causality and animacy. Trends in Cognitive Sciences 4, 8, 299–309.Google ScholarCross Ref
    22. Shum, H. P. H., Komura, T., Shiraishi, M., and Yamazaki, S. 2008. Interaction patches for multi-character animation. ACM Trans. Graph. 27, 5 (Dec.), 114:1–114:8. Google ScholarDigital Library
    23. Shum, H. P., Komura, T., and Yamazaki, S. 2012. Simulating multiple character interactions with collaborative and adversarial goals. IEEE Transactions on Visualization and Computer Graphics 18, 741–752. Google ScholarDigital Library
    24. Sok, K. W., Yamane, K., Lee, J., and Hodgins, J. 2010. Editing dynamic human motions via momentum and force. In Proc. of SCA ’10, 11–20. Google ScholarDigital Library
    25. Therien, J., and Bernard, S. 2008. Taming the mob: Creating believable crowds in assassins creed. Presented at Game Developers Conference, San Francisco, CA, Feb 18-22.Google Scholar
    26. Yeh, T. Y., Reinman, G., Patel, S. J., and Faloutsos, P. 2009. Fool me twice: Exploring and exploiting error tolerance in physics-based animation. ACM Trans. Graph. 29, 1 (Dec.), 5:1–5:11. Google ScholarDigital Library
    27. Yin, K., Pai, D. K., and Panne, M. V. D. 2005. Data-driven interactive balancing behaviors. In Pacific Graphics 05.Google Scholar
    28. Zordan, V. B., and Hodgins, J. K. 2002. Motion capture-driven simulations that hit and react. In Proc. of SCA ’02, 89–96. Google ScholarDigital Library
    29. Zordan, V. B., Majkowska, A., Chiu, B., and Fast, M. 2005. Dynamic response for motion capture animation. ACM Trans. Graph. 24, 3 (July), 697–701. Google ScholarDigital Library

ACM Digital Library Publication:

Overview Page: