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Proceedings Paper

A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment
Author(s): Lei Cai; Lin Wang; Bo Li; Libao Zhang; Wen Lv
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Paper Abstract

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can’t be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

Paper Details

Date Published: 26 June 2017
PDF: 7 pages
Proc. SPIE 10334, Automated Visual Inspection and Machine Vision II, 103340K (26 June 2017); doi: 10.1117/12.2270097
Show Author Affiliations
Lei Cai, Research Institute of Highway (China)
Lin Wang, Research Institute of Highway (China)
Bo Li, Beijing Normal Univ. (China)
Libao Zhang, Beijing Normal Univ. (China)
Wen Lv, Beijing Normal Univ. (China)

Published in SPIE Proceedings Vol. 10334:
Automated Visual Inspection and Machine Vision II
Jürgen Beyerer; Fernando Puente León, Editor(s)

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