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ICASSP
2011
IEEE

Efficient block-division model for robust multiple object tracking

8 years 3 months ago
Efficient block-division model for robust multiple object tracking
Tracking multiple objects under occlusion is one of the most challenging issues in computer vision. Occlusion results in mistaken match when finding the most similar candidate. Adapting to the change of objects is essential for tracking as objects often undergo intrinsic changes, but noise is unavoidably introduced during updating of the object, and this further confuses the tracker. In order to address these problems, a block-division appearance model is introduced to efficiently handle occlusion. In this model, spatial information is introduced to avoid the mistaken match between object and candidate. Based on this model, a selective updating strategy is proposed to incrementally learn the change of the object, avoiding introducing noise when updating. At the same time occlusion is deduced by monitoring the variation of each block. Experimental results in various videos validate the effectiveness of our algorithm in tracking multiple objects under occlusion.
Wenhan Luo, Xiaoqin Zhang, Yang Liu, Xi Li, Weimin
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Wenhan Luo, Xiaoqin Zhang, Yang Liu, Xi Li, Weiming Hu, Wei Li
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