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Temporal Analysis of Motion in Video Sequences through Predictive Operators

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Abstract

We study the problem of recovering temporal parameters which act as predictive operators, generalize time-to-collision and have direct interpretation for navigational purposes for piecewise arbitrarily smooth (polynomial) motion. A result stating that, for monocular observers undergoing arbitrary polynomial laws, these parameters are visually observable, is presented in the first part of this paper. This property suggests an alternate temporal representation of visual looming information. The second part of this paper is concerned with algorithmic approaches for environments with maneuvering agents. A method addressing model order determination, collision detection, and temporal parameter estimation is proposed. Experimental results are reported.

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References

  • Bar-Shalom, Y. and Fortmann, T.E. 1988. Tracking and Data Association. Academic Press: New York, NY.

    Google Scholar 

  • Cipolla, R. 1996. Active Visual Inference of Surface Shape. Lecture Notes in Computer Science. Springer-Verlag.

  • Duric, Z., Rosenfeld, A., and Duncan, J. 1994. The applicability of Green'stheorem to computation of rate of approach. In Proc. DARPA Image Understanding Workshop, Monterey, CA, Morgan Kaufmann Publisher, pp. 1209–1217.

    Google Scholar 

  • Francois, E. and Bouthemy, P. 1990. Derivation of qualitative information in motion analysis. Image and Vision Computing, 8:279– 288.

    Google Scholar 

  • Gibson, J.J. 1979. The Ecological Approach to Visual Perception. Houghton Mifflin: Boston.

    Google Scholar 

  • Hervé, J.Y., Sharma, R., and Cucka, P. 1991. The geometry of visual coordination. In Proc. AAAI National Conference on Artificial Intelligence, pp. 732–737.

  • Horn, B.K.P and Schunck, B.G. 1981. Determining optical flow. Artificial Intelligence, 17:185–203.

    Google Scholar 

  • Kailath, T. 1980. Linear Systems. Prentice-Hall.

  • Koenderink, J.J. 1986. Optic flow. Vision Research, 26:161–168.

    Google Scholar 

  • Lee, D.N. 1976. A theory of visual control of braking based on information about time to contact. Perception, 5:436–459.

    Google Scholar 

  • Lee, D.N. and Reddish, P.E. 1981. Plummeting gannets: A paradigm of ecological optics. Nature, 293:293–294.

    Google Scholar 

  • Maybank, S.J. 1987. Apparent area of a rigid moving body. Image and Vision Computing, 5:111–113.

    Google Scholar 

  • Meyer, F.G. 1994. Time-to-collision from first order models of the motion field. IEEE Trans. on Robotics and Automation, 10:792– 798.

    Google Scholar 

  • Nelson, R.C. and Aloimonos, J.Y. 1989. Obstacle avoidance using flow field divergence. IEEE Trans. Pattern Analysis and Machine Intelligence, 2:1102–1106.

    Google Scholar 

  • Poggio, T., Verri, A., and Torre, V. 1991. Green theorems and qualitative properties of the optical flow. AI Memo 1289, MIT AI Laboratory.

  • Subbarao, M. 1990. Bounds on time-to-collision and rotational component from first order derivatives of image flow. Computer Vision, Graphics and Image Processing, 50:329–341.

    Google Scholar 

  • Tistarelli, M. and Sandini, G. 1993. On the advantages of polar and log-polar mapping for direct estimation of time-to-impact from optical flow. IEEE Trans. Pattern Analysis and Machine Intelligence, 15:401–410.

    Google Scholar 

  • Yao, Y.S., Burlina, P., and Chellappa, R. 1995. Electronic image stabilization using multiple visual cues. In Proc. International Conference on Image Processing, Crystal City, VA, pp. 191– 194.

  • Zheng, Q. and Chellappa, R. 1993. A computational vision approach to image registration. IEEE Trans. Image Processing, 2(3):311–326.

    Google Scholar 

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Burlina, P., Chellappa, R. Temporal Analysis of Motion in Video Sequences through Predictive Operators. International Journal of Computer Vision 28, 175–192 (1998). https://doi.org/10.1023/A:1008067101494

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