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Proceedings Paper

Vision-based vehicle tracking via a noise-tolerant optical flow method
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Paper Abstract

Vehicle-tracking is defined as an autonomous vehicle following a lead vehicle based on the observed range and heading angle of the lead vehicle. This paper presents a vision-based vehicle tracking algorithm for obtaining the range and heading angle information. The developed algorithm utilizes the minimization of an energy function reflecting the optical flow of a specified shape on the lead vehicle and the gradient of its edges. The embedded optical flow method is capable of tolerating intensity variations or environmental noise generated by light and background sources. This noise tolerance is achieved by employing a response function which adapts to the distribution of a similarity measure within a moving search window. Several examples are shown to illustrate the performance of this tracking algorithm in realistic outdoor scenes.

Paper Details

Date Published: 16 June 1995
PDF: 9 pages
Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); doi: 10.1117/12.211978
Show Author Affiliations
Nasser Kehtarnavaz, Texas A&M Univ. (United States)
Jeong-Tae Kim, Texas A&M Univ. (United States)

Published in SPIE Proceedings Vol. 2488:
Visual Information Processing IV
Friedrich O. Huck; Richard D. Juday, Editor(s)

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