Synchronization analysis by direction classification of human motion based on optical flows

Abstract

For the human motion detection by camera, it is usually needed to use sensors and/or markers. We propose a method that does not handle any sensors nor markers, instead, that adopts optical flows. By applying this method, we can analyze synchronization between human motions and classify moving direction of crowds. The optical flows are estimated by the Lucas-Kanade method. The result of the optical flows is assigned to a hue circle, and the histogram of the hue gives information to identify human motions. Utilizing this color information makes our method robust to the environmental changes. We defined the combined Bhattacharyya coefficient and use it to detect the synchronization of the human motions. In this paper, two persons dance choreography and the results before and after the practices are quantitatively evaluated. The crowds' classification is performed depending on the moving directions of the crowds. We also describe the method to detect unusual acts. These functions are available to score the group performances in games and to detect the persons doing normal and abnormal actions.