MOTION ESTIMATION AND DETECTION OF COMPLEX OBJECT BY ANALYZING RESAMPLED MOVEMENTS OF PARTS

Abstract

A moving object that has many complex moving parts is very hard to detect and its motion is not easy to estimate. In this paper, we present a new technique for motion estimation and detection of moving complex objects by analyzing the resampled motions of the parts of objects. The Kalman filter is used to track all resampled movements and the tracked routes are classified into groups that share the same fundamental movements. Our simulation show that recall of motion estimation and detection is approximately 0.8, while the computation drops exponentially. 1