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http://dx.doi.org/10.5391/JKIIS.2006.16.3.266

Gait Recognition using Modified Motion Silhouette Image  

Hong Sung-Jun (연세대학교 전기전자공학부)
Lee Hee-Sung (연세대학교 전기전자공학부)
Oh Kyong-Sae (연세대학교 전기전자공학부)
Kim Eun-Tai (연세대학교 전기전자공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.16, no.3, 2006 , pp. 266-270 More about this Journal
Abstract
In this paper, we propose the human identification system based on Hidden Markov model using gait. Since each gait cycle consists of a set of continuous motion states and transition across states has probabilistic dependences, individual gait can be modeled using Hidden Markov model. We assume that individual gait consists of N discrete transitions and we propose gait feature representation, Modified Motion Silhouette Image (MMSI) to represent and recognize individual gait. MMSI is defined as a gray-level image and it provides not only spatial information but also temporal information. The experimental results show gait recognition performance of proposed system.
Keywords
Gait Recognition; Hidden Markov Model; Motion Analysis; Motion Silhouette Image;
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