期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：2
页码：189-202
DOI：10.14257/ijsip.2016.9.2.17
出版社：SERSC
摘要：Most researches on human behavior recognition are mainly based on the features of whole body motion. This paper proposed a hierarchical discriminative approach for recognizing human behavior based on limbs motion. The approach consists of feature extraction with mutual motion pattern analysis and discriminative behavior modeling in the hierarchical manifold space. A cascade CRF is introduced to estimate the motion patterns in the corresponding manifold subspace, and the trained SVM classifier is used to predict the behavior label for the current observation. The results on motion capure data prove the significance motion analysis of body parts, and the results on synthetic image sequences are also presented to demonstrate the robustness of the proposed algorithm.
关键词：human behavior analysis; image sequence; support vector machine
