Human motion analysis using dynamic textures

Abstract

Human motion analysis is a dynamic field of research in computer vision. Its popularity is because of wide application in surveillance, study of social interaction, robot guidance and video indexing. Human motion can be considered as dynamic texture since it has statistical variation in spatiotemporal domain. The local interest features contain efficient information of these spatiotemporal variations. The proposed method is based on dynamic texture description for analysis of human motion using visual dictionary. This method is applied to two major applications: action recognition and gait recognition. We evaluate the performance of our method on KTH dataset for both action and gait recognition.