Hidden Markov model for the detection and tracking of highway vehicles in image sequences

Wai Ying Kan; James V. Krogmeier; Peter C. Doerschuk

doi:10.1117/12.258229

14 November 1996 Hidden Markov model for the detection and tracking of highway vehicles in image sequences

Wai Ying Kan, James V. Krogmeier, Peter C. Doerschuk

Proceedings Volume 2847, Applications of Digital Image Processing XIX; (1996) https://doi.org/10.1117/12.258229
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

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.

Citation Download Citation

Wai Ying Kan, James V. Krogmeier, and Peter C. Doerschuk "Hidden Markov model for the detection and tracking of highway vehicles in image sequences", Proc. SPIE 2847, Applications of Digital Image Processing XIX, (14 November 1996); https://doi.org/10.1117/12.258229

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