Human action recognition employing 2DPCA and VQ in the spatio-temporal domain

In this paper a novel algorithm for human action recognition is presented. This approach is based on Two-Dimensional Principal Component Analysis (2DPCA) and Vector Quantization (VQ) in the spatial-temporal domain. This method reduces computational complexity by a factor of 98, while maintaining the storage requirement and the recognition accuracy, compared with some of the most recent approaches in the field. Experimental results applied on the Weizmann dataset confirm the excellent properties of the proposed algorithm.