Detecting kinetic occlusion

Visual motion boundaries provide a powerful cue for the perceptual organization of scenes. Motion boundaries are present when surfaces in motion occlude one another. Conventional approaches to motion analysis have relied on assumptions of data conservation and smoothness, which has made analysis of motion boundaries difficult. We show that a common source of motion boundary, kinetic occlusion, can be detected using spatiotemporal junction analysis. Junction analysis is accomplished by utilizing distributed representations of motion used in models of human visual motion sensing. By detecting changes in the direction of motion in these representations, spatiotemporal junctions are detected in a manner which differentiates accretion from deletion. We demonstrate successful occlusion detection on spatiotemporal imagery containing occluding surfaces in motion