Tracking objects in occluding environments using temporal spatio-velocity transform

This paper presents a methodology for tracking moving objects in an occluded environment when occlusion occurs. We analyze sequences in which physical obstacles such as fences and trees divide an object into several blobs, both spatially and temporally. Our system successfully tracks the divided blobs as one object and reconstructs the whole object. We use the temporal spatio-velocity (TSV) transform and a cylinder model of object trajectories. The TSV transform extracts pixels with stable velocities and removes noisy pixels with unstable velocities. The cylinder model connects several blobs into one object and associates blobs that are occluded for a long period of time. We present results in which moving persons and vehicles occluded by fences and trees are successfully tracked even when the occlusion lasts for as long as 100 frames.