Tensor analysis and multi-scale features based multi-view human action recognition

A method of multi-view human action recognition based on multi-scale features via tensor analysis is proposed. A series of silhouettes are transformed to a Serials-Frame image, from which the multi-scale features are extracted to construct the eigenSpace of a tensor, which named Serials-Frame Tensor (SF-Tensor). The SF-Tensor subspace analysis is applied to separate the variable views and people information to recognize different actions. Experiment results obtained show that the proposed method attains a good recognition rate and improves the efficiency significantly.