A tensor-driven active contour model for moving object segmentation

In this paper we propose an approach to the segmentation of video objects based on motion cues. Motion analysis is performed by estimating local orientations in the spatio-temporal domain using the three-dimensional structure ten-sor. These estimates are integrated as an external force into an active contour model, thus stopping the evolving curve when it reaches the moving object’s boundary. To enable si-multaneous detection of several objects, we reformulate the tensor-based active contour model using the level-set tech-nique. In addition, a contour refinement technique has been developed to better approximate the real boundary of the moving object. We provide promising experimental results calculated on real-world video sequences widely used within the com-puter vision community. 1