Spatiotemporal junction analysis for motion boundary detection

Abstract

Conventional approaches to 2-D motion estimation have relied on assumptions of data conservation and smoothness, which has made analysis of motion boundaries difficult. We propose that one of the cues present at motion boundaries, kinetic occlusion, can be detected using spatiotemporal junction analysis. Junction analysis is accomplished by constructing distributed representations of motion, and spatiotemporally filtering these signals to detect orientation stopping or starting in space-time. Our occlusion detection scheme differentiates accretion from deletion of surface texture at motion boundaries. We demonstrate successful motion boundary extraction on spatiotemporal stimuli containing occluding surfaces in motion.