Estimation of Accelerated Motion and Occlusions from Time-Varying Images

This thesis addresses the problem of modeling and computing dense 2-D velocity and acceleration fields from time-varying images and applying them to motioncompensated interpolation. Unlike in many other approaches that assume motion to be locally translational, the approach proposed here uses a quadratic motion trajectory model that incorporates both velocity and acceleration. This model corresponds better to natural image sequences especially when processing over multiple frames is considered. One of the advantages of using accelerated motion over linear trajectories is in motion-compensated processing over multiple images. This is due to the fact that over longer time frame, a quadratic motion model is capable of providing a better intensity match along trajectories than the linear model. The side effect is, however, that with more images used for estimation occlusion effects play a more dominant role. Therefore, another motion model is proposed to account for occlusions and motion d..