Rotational and translational motion estimation and selective reconstruction in digital image sequences

This paper addresses the problem of motion estimation and selective reconstruction of objects undergoing rotational motion composed with translational motion. The goal is to derive the motion parameters belonging to the multiple moving objects, i.e. the angular velocities and the translational velocities and identify their locations at each time instance by selective reconstruction. These parameters and locations can be used for various purpose such as trajectory tracking, focus/shift attention of robot, etc. The innovative algorithm we have developed is based on angular velocity and translational velocity tuned 2D+T filters. One of the important facts about the algorithm is that it is effective for both spinning motion and orbiting motion, and thus unifies the treatment of the two kinds of rotational motion. Also by tuning of the filters, we can derive the translational motion parameters and the rotational motion parameters separately, which has the advantage of making motion estimation faster and more robust compared to estimating all of them simultaneously. The algorithm is simulated using synthesized image sequences corrupted by noise and is shown to be accurate and robust against noise and occlusion