Computationally scalable partial distance based fast search motion estimation
We present a class of algorithms that use a partial distance metric to speedup the motion estimation process. The partial distance metric is used within the motion search to eliminate unlikely candidates through a thresholding process that enables computation scalability. We also propose a multiresolution variant which further reduces the complexity. Our results are comparable to state of the art approaches present a regular structure and are computationally scalable.