A queue-based block matching algorithm for video compression and motion segmentation

This paper addresses two issues related to motion estimation using the block matching algorithms (BMA): (1) determining the reliability of the motion vectors of each block, and (2) imposing smoothness constraint to the motion vector field. We introduce a new robust reliability measure to represent the confidence level of the motion vector from the cost function distribution and propose a novel algorithm that incorporates smoothness constraint into the motion vector field evaluation by implementing a priority queue structure based on the reliability measure. In this framework, a smooth motion vector field is evaluated in a single pass without going through iterations typical of many existing optical flow estimation algorithms. Hence it is fast and can easily be incorporated into real-time applications for video compression as well as image segmentation.