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Segmentation and tracking of interacting human body parts under occlusion and shadowing

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2 Author(s)
Park, S. ; Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA ; Aggarwal, J.K.

The paper presents a system to segment and track multiple body parts of interacting humans in the presence of mutual occlusion and shadow. The color image sequence is processed at three levels: pixel level, blob level, and object level. A Gaussian mixture model is used at the pixel level to train and classify individual pixel colors. A Markov random field (MRF) framework is used at the blob level to merge the pixels into coherent blobs and to register inter-blob relations. A coarse model of the human body is applied at the object level as empirical domain knowledge to resolve ambiguity due to occlusion and to recover from intermittent tracking failures. A two-fold tracking scheme is used which consists of blob to blob matching in consecutive frames and blob to body part association within a frame. The tracking scheme resembles a multi-target, multi-assignment framework. The result is a tracking system that simultaneously segments and tracks multiple body parts of interacting people. Example sequences illustrate the success of the proposed paradigm.

Published in:

Motion and Video Computing, 2002. Proceedings. Workshop on

Date of Conference:

5-6 Dec. 2002