Vector field analysis for motion pattern identification in video

Identification of motion patterns in video is an important problem because it is the first step towards analysis of complex multi-person behaviors to obtain long-term interaction models. In this paper, we will present a flow based technique to identify spatio-temporal motion patterns in a multi-object video. We use the Helmholtz decomposition of optical flow and compute singular points corresponding to component fields. We will show that the optical flow can be used to identify regions which correspond to different moving entities in the video. The singular points in these regions capture the characteristics of the field around them and can be used to identify these regions. This representation would provide us with a framework to analyze activities of individual entities in the scene as well as the global interactions between them. We demonstrate our algorithm on a dataset composed of multi-object videos recorded in a realistic environment.