An efficient true-motion estimator using candidate vectors from a parametric motion model

Abstract

Some efficient motion estimation algorithms select their output motion vector from a limited number of likely correct candidate, or prediction, vectors. In this paper, next to the known spatial and temporal prediction vectors, an additional and independent prediction is proposed. This candidate is generated with a parametric model describing the global motion in a previously estimated motion vector field. The proposal is elaborated as an addition to the three-dimensional (3-D) recursive search block-matching algorithm. The evaluation shows that a subpixel accurate, true-motion estimator results with a very low operations count.