Video object tracking via central macro-blocks and directional vectors

Authors:
B. Zhang;J. Jiang;G. Xiao
Affiliations:
Faculty of Informatics & Computing, Southwest University, Chongqing, China;Faculty of Informatics & Computing, Southwest University, Chongqing, China and Department of EIMC, University of Bradford, UK;Faculty of Informatics & Computing, Southwest University, Chongqing, China
Venue:
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Year:
2007

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Abstract

While existing video object tracking is sensitive to the accuracy of object segmentation, we propose a central point based algorithm in this paper to allow inaccurately segmented objects to be tracked inside video sequences. Since object segmentation remains to be a challenge without any robust solution to date, we apply a region-grow technique to further divide the initially segmented object into regions, and then extract a central point within each region. A macro-block is formulated via the extracted central point, and the object tracking is carried out through such centralized macroblocks and their directional vectors. As the size of the macroblock is often much smaller than the segmented object region, the proposed algorithm is tolerant to the inaccuracy of object segmentation. Experiments carried out show that the proposed algorithm works well in tracking video objects measured by both efficiency and effectiveness.