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Proceedings Paper

Hidden Markov model for the detection and tracking of highway vehicles in image sequences
Author(s): Wai Ying Kan; James V. Krogmeier; Peter C. Doerschuk
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Paper Abstract

Motivated by recent interest in intelligent transportation systems, this paper considers the problem of tracking diverse vehicles as they traverse a roadway instrumented with video cameras. From vehicle tracks it is straight- forward to compute basic traffic parameters such as flow, speed, and concentration. The vehicles to be tracked can be dense and we assume that computational resources are limited. Therefore, we cannot consider 3D processing but rather must partition the problem as much as possible into 1D or 2D problems. The key simplifying aspect is that the vehicles follow known tracks.

Paper Details

Date Published: 14 November 1996
PDF: 9 pages
Proc. SPIE 2847, Applications of Digital Image Processing XIX, (14 November 1996); doi: 10.1117/12.258229
Show Author Affiliations
Wai Ying Kan, Purdue Univ. (United States)
James V. Krogmeier, Purdue Univ. (United States)
Peter C. Doerschuk, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 2847:
Applications of Digital Image Processing XIX
Andrew G. Tescher, Editor(s)

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