標題: A language modeling approach to atomic human action recognition
作者: Liang, Yu-Ming
Shih, Sheng-Wen
Shih, Arthur Chun-Chieh
Liao, Hong-Yuan Mark
Lin, Cheng-Chung
資訊工程學系
Department of Computer Science
關鍵字: human behavior analysis;language modeling;posture template selection;variable-lenth Markov mode
公開日期: 2007
摘要: Visual analysis of human behavior has generated considerable interest in the field of computer vision because it has a wide spectrum of potential applications. Atomic human action recognition is an important part of a human behavior analysis system. In this paper, we propose a language modeling framework for this task. The framework is comprised of two modules: a posture labeling module, and an atomic action learning and recognition module. A posture template selection algorithm is developed based on a modified shape context matching technique. The posture templates form a codebook that is used to convert input posture sequences into training symbol sequences or recognition symbol sequences. Finally, a variable-length Markov model technique is applied to learn and recognize the input symbol sequences of atomic actions. Experiments on real data demonstrate the efficacy of the proposed system.
URI: http://hdl.handle.net/11536/11701
http://dx.doi.org/10.1109/MMSP.2007.4412874
ISBN: 978-1-4244-1273-0
DOI: 10.1109/MMSP.2007.4412874
期刊: 2007 IEEE NINTH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING
起始頁: 288
結束頁: 291
顯示於類別:會議論文


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