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

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.