Circular Viterbi based adaptive system for automatic video object segmentation

Many future video standards such as MPEG-4 are shifting focus from compression to content; video object segmentation is the key technology required by these standards. Unlike still images, motion in video can be used to discriminate between objects. We present an automatic video single object segmentation system whose core is the adaptive version of the circular Viterbi algorithm. The circular Viterbi algorithm fuses the information from motion analysis, edge analysis, active contours (dynamic snake), and temporal correlation into a unified system. Results of pixel-resolution boundaries from our system are shown. Analysis of results, the integration of human-guided data and region-based analysis and a future iterative scheme for multiple object sequences are also discussed