A tracking based fast online complete video synopsis approach

By segmenting moving objects out and then densely stitching them into background frames, video synopsis provides an efficient way to condense long videos while preserving most activities. Existing video synopsis methods, however, often suffer from either high computation cost due to global energy minimization or unsatisfactory condense rate to avoid loss of important object activities. To address these problems, a tracking based fast online video synopsis approach is proposed in this paper which makes following three main contributions: 1) an online formulation of the video synopsis problem which makes the approach very fast and scalable to endless surveillance videos with reduced chronological disorders, 2) a tracking based schema which can preserve most object activities, and 3) a complete optimization process from both temporal and spatial redundancies of the video which results in much higher condense rate and less object conflict rate. Experimental results demonstrate the effectiveness and efficiency of proposed approach compared to the traditional method on public surveillance videos.