A tensor-driven active contour model for moving object segmentation

We propose an approach to the segmentation of video objects based on motion cues. Motion analysis is performed by estimating local orientations in the spatiotemporal domain using the three-dimensional structure tensor. 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 simultaneous detection of several objects, we reformulate the tensor-based active contour model using the level-set technique. 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 computer vision community