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 |