Long-term moving object segmentation and tracking using spatio-temporal consistency

Abstract

The success of object-based media representation and description (e.g., MPEG-4 and -7) depends largely on effective object segmentation tools. We expand our previous work on automatic video region tracking and develop a robust-moving objects detection system. In our system, we first utilize innovative methods of combining color and edge information in improving the object motion estimation results. Then we use the long-term spatio-temporal constraints to achieve reliable object tracking over long sequences. Our extensive experiments demonstrate excellent results in handling challenging cases in general domains (e.g., stock footage) including depth-varying multi-layer background and fast camera motion.