JACIII Vol.8 No.5 pp. 469-476
doi: 10.20965/jaciii.2004.p0469


Motion-Based Template Matching for Obstacle Detection

Kazuhiko Kawamoto*, Naoya Ohnishi**, Atsushi Imiya**,***, Reinhard Klette****, and Kaoru Hirota*

*Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Mail-Box G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan

**Institute of Media and Information Technology, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan

***Software Research Division, National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan

****Centre for Image Technology and Robotics, University of Auckland, Tamaki Campus, Building 731, Auckland, New Zealand

August 31, 2003
April 20, 2004
September 20, 2004
template matching, optical flow, obstacle detection, median filtering
A matching algorithm that evaluates the difference between model and calculated flows for obstacle detection in video sequences is presented. A stabilization method for obstacle detection by median filtering to overcome instability in the computation of optical flow is also presented. Since optical flow is a scene-independent measurement, the proposed algorithm can be applied to various situations, whereas most of existing color- and texture-based algorithms depend on specific scenes, such as roadway and indoor scenes. An experiment is conducted with three real image sequences, in which a static box or a moving toy car appears, to evaluate the performance in terms of accuracy under varying thresholds using a receiver operating characteristic (ROC) curve. For the three image sequences, the ROC curves show, in the best case, that the false positive fraction and the true positive fraction is 19.0% and 79.6%, 11.4% and 84.5%, 19.0% and 85.4%, respectively. The processing time per frame is 19.38msec. on 2.0GHz Pentium 4, which is less than the video-frame rate.
Cite this article as:
K. Kawamoto, N. Ohnishi, A. Imiya, R. Klette, and K. Hirota, “Motion-Based Template Matching for Obstacle Detection,” J. Adv. Comput. Intell. Intell. Inform., Vol.8 No.5, pp. 469-476, 2004.
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