Flow estimation for motion analysis on compressed domain

Because video sequences consist of dynamic video objects in nature, video object motion is an effective feature in describing the content of video sequences. In this paper, we propose a method that converts motion vectors (MVs) on MPEG coded domain to a uniform set, independent of the frame type and the direction of prediction, and directly utilizes these normalized MVs (N-MVs) in understanding video contents. To obtain such uniform MV set, we proposed a new motion analysis method using Bi-directional Prediction-Independent Framework. Generally, it is impossible to directly compare an I frame without MV to other frame types such as B or P frame. But, our approach enables a frame-type independent representation that normalizes temporal features including frame type, MB encoding and MVs. In the experiments, we show that the proposed method is better than the conventional one in terms of performance.