Joint registration and active contour segmentation for object tracking

This paper presents a novel object tracking framework by joint registration and active contour segmentation (JRACS), which can robustly deal with the non-rigid shape changes of the target. The target region, which includes both foreground and background pixels, is implicitly represented by a level set. A Bhattacharyya similarity based metric is proposed to locate the region whose foreground and background distributions best match those of the tracked target. Based on this metric, a tracking framework that consists of a registration stage and a segmentation stage is then established. The registration step roughly locates the target object by modeling its motion as an affine transformation, and the segmentation step refines the registration result and computes the true contour of the target. The robust tracking performance of the proposed JRACS method is demonstrated by real video sequences where the objects have clear non-rigid shape changes.