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Human pose recognition by memory-based hierarchical feature matching

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4 Author(s)
Urano, T. ; Dept. of Mech. Eng., Tokyo Univ. of Sci., Japan ; Matsui, T. ; Nakata, T. ; Mizoguchi, H.

A human posture recognition system based on a memory-based approach is studied. Human body images extracted by depth data are labeled and stored in a database together with compressed feature values consist of higher-order local correlation values and outline diameters. The compressed features are used to speed up the database search in a hierarchical manner. The system can classify human body postures into 6 categories in the experiment. The system was robust against change of humans and light condition.

Published in:

Systems, Man and Cybernetics, 2004 IEEE International Conference on  (Volume:7 )

Date of Conference:

10-13 Oct. 2004