Human Action Recognition Using Dynamic Time Warping and Voting Algorithm (1)

Abstract

This paper presents a human action recognition method using dynamic time warping and voting algorithms on 3D human skeletal models. In this method human actions, which are the combinations of multiple body pa rt movements, are described by feature matrices concer ning both spatial and temporal domains. The feature matrices are created based on the spatial selection of relative angles between body parts in time seri es. Then, action recognition is done by applying a classifier which is the combination of dynamic time warping ( DTW) and a voting algorithm to the feature matrices. Exp erimental results show that the performance of our action recognition method obtains high recognition accurac y at reliable computation speed and can be applied in real time human action recognition systems.