Edge Tracking for Motion Segmentation and Depth Ordering

This paper presents a new theoretical framework for motion segmentation based on the motion of tracked region edges. By considering the visible edges of an object, constraints may be placed on the motion labelling of edges. This enables the most likely region labelling and layer ordering to be established, thus producing a segmentation. An implementation is outlined and demonstrated on test sequences containing two motions. The image is divided into regions using a colour edgebased segmentation scheme and the normal motion of these edges is tracked. The EM algorithm is used to partition the edges and fit the best two motions accordingly. Hypothesising each motion in turn to be the foreground motion, the labelling constraints can be applied and the frame segmented. The hypothesis which best fits the observed edge motions indicates the layer ordering and leads to a very accurate segmentation.