Discriminative key pose extraction using extended LC-KSVD for action recognition

Authors

Lijuan Zhou, University of WollongongFollow
Wanqing Li, University of WollongongFollow
Yuyao Zhang, University of WollongongFollow
Philip O. Ogunbona, University of WollongongFollow
Duc Thanh Nguyen, University of WollongongFollow
Hanling Zhang, Human University

RIS ID

97519

Publication Details

Zhou, L., Li, W., Zhang, Y., Ogunbona, P. O., Nguyen, D. & Zhang, H. (2014). Discriminative dey pose extraction using extended LC-KSVD for action recognition. 2014 International Conference on digital Image Computing: Techniques and Applications (DICTA 2014) (pp. 1-8). United States: Institute of Electrical and Electronics Engineers.

Abstract

This paper presents a method for extracting discriminative key poses for skeleton-based action recognition. Poses are represented by normalized joint locations, velocities and accelerations of skeleton joints. An extended label consistent K-SVD (ELC-KSVD) algorithm is proposed for learning the common and action-specific dictionaries. Discriminative key poses are represented by the atoms of the action-specific dictionaries. With the specific dictionaries, sparse codes are obtained for representing action instances through max pooling and temporal pyramid. A SVM classifier is trained for action recognition. The proposed method was evaluated on the MSRC-12 gesture and MSR-Action 3D datasets. Experimental results have shown that the proposed method is effective in extracting discriminative key poses.