Multiple Human Objects Tracking in Crowded Scenes

Authors:
Yao-Te Tsai;Huang-Chia Shih;Chung-Lin Huang
Affiliations:
National Tsing Hua University;National Tsing Hua University;National Tsing Hua University
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Year:
2006

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Pattern Recognition Letters

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Abstract

This paper introduces a multiple human objects tracking system to detect and track multiple objects in the crowded scene in which occlusions occur. Our method assign each pixel to different human object based on its relative distance to that object and the corresponding color model. If no occlusion, we easily track each object independently based on each segmented object region and optical flow. With occlusion, we analyze the color distribution of the occlusion group to differentiate each object in the group. By calculating the distances between objects, we can determine whether an object is separated from the occlusion group and to be tracked individually afterwards.