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2006
IEEE

Understanding Human Behavior Using a Language Modeling Approach

12 years 5 months ago
Understanding Human Behavior Using a Language Modeling Approach
Visual analysis of human behavior has generated considerable interest in the field of computer vision because of the wide spectrum of potential applications. In this paper, we present a language modeling framework for understanding human behavior. The proposed framework consists of two modules: the key posture selection module, and the variable-length Markov model (VLMM) behavior recognition module. A key posture selection algorithm is developed based on the shape context matching technique. A codebook is then constructed with the computed key postures and used to convert input image sequences into training symbol sequences or recognition symbol sequences. Finally, a VLMM is applied to learn and recognize the constructed symbol sequences corresponding to human behavior patterns. Experiments on real data demonstrate the efficacy of the proposed system.
Yu-Ming Liang, Sheng-Wen Shih, Arthur Chun-Chieh S
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where iihmsp
Authors Yu-Ming Liang, Sheng-Wen Shih, Arthur Chun-Chieh Shih, Hong-Yuan Mark Liao
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