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Proceedings Paper

Vehicle tracking process based on combination of SURF and color feature
Author(s): Xiaofeng Lu; Lei Wang
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Paper Abstract

In this paper, we describe a novel method for visual vehicle tracking process based on the combination of speeded-up robust features (SURF) points and color feature. The whole tracking process is constructed in the framework of particle filter. To further improve the precision and stability of tracking, a dynamic update mechanism of target template is proposed to capture appearance changes. This mechanism includes two strategies: Adopting new feature points and discarding bad feature points. A novel distance kernel function method is adopted to allocate the weight of each particle, and to improve the stability of the tracking template. The experiments present that our algorithm can track the targets more robustly and adaptively than the traditional algorithms.

Paper Details

Date Published: 4 March 2015
PDF: 7 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430W (4 March 2015); doi: 10.1117/12.2178870
Show Author Affiliations
Xiaofeng Lu, Xi'an Univ. of Technology (China)
Lei Wang, Xi'an Univ. of Technology (China)


Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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