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Upper Body Tracking Using Hierarchical Sample Propagation Method and Pose Recognition  

Cho, Sang-Hyun (Department of Computer Engineering, The Catholic University of Korea)
Kang, Hang-Bong (Department of Computer Engineering, The Catholic University of Korea)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.45, no.5, 2008 , pp. 63-71 More about this Journal
Abstract
In this paper, we propose a color based hierarchically propagated particle filter that extends the color based particle filter into the articulated upper body tracking. Since color feature is robust to partial occlusion and rotation, the color based particle filter is widely used for object tracking. However, in articulated body tacking, it is not desirable to use the traditional particle filter because the dimension of the state vector usually is high and thus, many samples are required for robust hacking. To overcome this problem, we use a hierarchical tracking method for each body part based on the blown body part. By using a hierarchical tracking method, we can reduce the number of samples for robust tracking in the cluttered environment. Also for human pose recognition, we classify the human pose into eight categories using Support Vector Machine(SVM) according to the angle between upper- arm and fore-arm. Experimental results show that our proposed method is more efficient than the traditional particle filter.
Keywords
body part tracking; pose recognition; SVM; particle filter; articulated body tracking;
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