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Proceedings Paper

A robust mean-shift tracking through occlusion and scale based on object trajectory for surveillance camera
Author(s): Hocine Labidi; Sen-Lin Luo; Mohamed Bachir Boubekeur
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Paper Abstract

Object tracking is an important part in surveillance systems, One of the algorithms used for this task is the meanshift algorithm due to the robustness, computational efficiency and implementation ease. However the traditional meanshift cannot effectively track the moving object when the scale changes, because of the fixed size of the tracking window, and can lose the target while an occlusion, In this study a method based on the trajectory direction of the moving object is presented to deal with the problem of scale change. Furthermore a histogram similarity metric is used to detect when target occlusion occurs, and a method based on multi kernel is proposed, to estimate which part is not in occlusion and this part will be used to extrapolate the motion of the object and gives an estimation of its position, Experimental results show that the improved methods have a good adaptability to the scale and occlusion of the target.

Paper Details

Date Published: 4 March 2015
PDF: 6 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432C (4 March 2015); doi: 10.1117/12.2179343
Show Author Affiliations
Hocine Labidi, Beijing Institute of Technology (China)
Sen-Lin Luo, Beijing Institute of Technology (China)
Mohamed Bachir Boubekeur, Beijing Institute 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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