“Self-animating images: illusory motion using repeated asymmetric patterns” by Chi, Lee, Qu and Wong

  • ©Ming-Te Chi, Tong-Yee Lee, Yingge Qu, and Tien-Tsin Wong




    Self-animating images: illusory motion using repeated asymmetric patterns



    Illusory motion in a still image is a fascinating research topic in the study of human motion perception. Physiologists and psychologists have attempted to understand this phenomenon by constructing simple, color repeated asymmetric patterns (RAP) and have found several useful rules to enhance the strength of illusory motion. Based on their knowledge, we propose a computational method to generate self-animating images. First, we present an optimized RAP placement on streamlines to generate illusory motion for a given static vector field. Next, a general coloring scheme for RAP is proposed to render streamlines. Furthermore, to enhance the strength of illusion and respect the shape of the region, a smooth vector field with opposite directional flow is automatically generated given an input image. Examples generated by our method are shown as evidence of the illusory effect and the potential applications for entertainment and design purposes.


    1. Backus, B. T., and Oruc, I. 2005. Illusory motion from change over time in the response to contrast and luminance. J. Vis. 5, 11 (12), 1055–1069.Google ScholarCross Ref
    2. Cabral, B., and Leedom, L. C. 1993. Imaging vector fields using line integral convolution. In Proceedings of ACM SIGGRAPH 1993, ACM Press / ACM SIGGRAPH, New York, NY, USA, 263–270. Google ScholarDigital Library
    3. Conway, B. R., Kitaoka, A., Yazdanbakhsh, A., Pack, C. C., and Livingstone, M. S. 2005. Neural basis for a powerful static motion illusion. J. Neurosci. 25, 23 (June), 5651–5656.Google ScholarCross Ref
    4. Faubert, J., and Herbert, A. M. 1999. The peripheral drift illusion: A motion illusion in the visual periphery. Perception 28, 617–621.Google ScholarCross Ref
    5. Fraser, A., and Wilcox, K. J. 1979. Perception of illusory movement. Nature 281, 565–566.Google ScholarCross Ref
    6. Freeman, W. T., Adelson, E. H., and Heeger, D. J. 1991. Motion without movement. In Computer Graphics (Proceedings of ACM SIGGRAPH 91), ACM, vol. 25, 27–30. Google ScholarDigital Library
    7. Gossett, N., and Chen, B. 2004. Self-animating line textures. Tech. rep. http://www.dtc.umn.edu/~gossett/publications/.Google Scholar
    8. Kitaoka, A., and Ashida, H. 2003. Phenomenal characteristics of the peripheral drift illusion. VISION (Journal of the Vision Society of Japan) 15, 261–262.Google Scholar
    9. Kitaoka, A., 2003. Rotating snakes. http://www.psy.ritsumei.ac.jp/~akitaoka/rotsnakee.html.Google Scholar
    10. Kitaoka, A. 2005. Trick Eyes Graphics. Tokyo: Kanzen.Google Scholar
    11. Kitaoka, A. 2006. Anomalous motion illusion and stereopsis. Journal of Three Dimensional Images (Japan) 20, 9–14.Google Scholar
    12. Kitaoka, A. 2006. The effect of color on the optimized fraser-wilcox illusion. the 9th L’ORE’AL Art and Science of Color Prize, 1–16.Google Scholar
    13. Lindbloom, B., 2007. Lab Gamut Display. http://brucelindbloom.com/LabGamutDisplay.html.Google Scholar
    14. Masuch, M. 1999. Speedlines: depicting motion in motionless pictures. In SIGGRAPH ’99: ACM SIGGRAPH 99 Conference abstracts and applications, ACM Press, New York, NY, USA, 277. Google ScholarDigital Library
    15. Mebarki, A., Alliez, P., and Devillers, O. 2005. Farthest point seeding for placement of streamlines. In Visualization, 2005. VIS 05. IEEE, 479–486.Google Scholar
    16. Murakami, I., Kitaoka, A., and Ashida, H. 2006. A positive correlation between fixation instability and the strength of illusory motion in a static display. Vision Research 46, 2421–2431.Google ScholarCross Ref
    17. Rusinkiewicz, S., Burns, M., and DeCarlo, D. 2006. Ex-aggerated shading for depicting shape and detail. ACM Transactions on Graphics 25, 3, 1199–1205. Google ScholarDigital Library
    18. Shoup, R. G. 1979. Color table animation. In Computer Graphics (Proceedings of ACM SIGGRAPH 79), ACM Press, 8–13. Google ScholarDigital Library
    19. Wei, L.-Y. 2006. Visualizing flow fields by perceptual motion. Tech. Rep. MSR-TR-2006-82, Microsoft Research, June.Google Scholar
    20. Xu, C., and Prince, J. 1997. Gradient vector flow: A new external force for snakes. In Proceedings of Computer Vision and Pattern Recognition (CVPR ’97), IEEE, 66–71. Google ScholarDigital Library

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