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Part-based multiple-person tracking with partial occlusion handling

6 years 12 months ago
Part-based multiple-person tracking with partial occlusion handling
Single camera-based multiple-person tracking is often hindered by difficulties such as occlusion and changes in appearance. In this paper, we address such problems by proposing a robust part-based tracking-by-detection framework. Human detection using part models has become quite popular, yet its extension in tracking has not been fully explored. Our approach learns part-based person-specific SVM classifiers which capture the articulations of the human bodies in dynamically changing appearance and background. With the part-based model, our approach is able to handle partial occlusions in both the detection and the tracking stages. In the detection stage, we select the subset of parts which maximizes the probability of detection, which significantly improves the detection performance in crowded scenes. In the tracking stage, we dynamically handle occlusions by distributing the score of the learned person classifier among its corresponding parts, which allows us to detect and predi...
Guang Shu, Afshin Dehghan, Omar Oreifej, Emily Han
Added 28 Sep 2012
Updated 28 Sep 2012
Type Journal
Year 2012
Where CVPR
Authors Guang Shu, Afshin Dehghan, Omar Oreifej, Emily Hand, Mubarak Shah
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