Combining procrustes shape analysis and shape context descriptor for silhouette-based gait recognition
A novel and powerful gait recognition algorithm is proposed. The method of procrustes shape analysis is used to produce procrustes mean shape (PMS) as a compressed representation of gait sequence. PMS is regarded as the gait signature for classification. Quite different and novel, instead of using the procrustes mean shape distance as a similarity measure, a novel shape descriptor, shape context, to measure the similarity between two PMSs is introduced. Experimental results show that the proposed algorithm outperforms other approaches in terms of recognition accuracy.