Cyclic Motion Detection Using Spatiotemporal Surfaces and Curves

Abstract

The problem of detecting cyclic motion, while recognized by the psychophysical community, has received very little attention in the computer vision community. In this paper cyclic motion is formally defined as repeating curvature values along a path of motion. A procedure is presented for cyclic motion detection using spatiotemporal (ST) surfaces and ST-curves. The projected movement of an object generates ST-surfaces. ST-curves are detected on the ST-surfaces, providing an accurate, compact, qualitative description of the ST-surfaces. Curvature scale-space of the ST-curves is then used to detect intervals of repeating curvature values. The successful detection of cyclic motion in two data sets is presented.