A Multiple-Frame Pel-Recursive Wiener-Based Displacement Estimation Algorithm

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Abstract
In this paper, a multiple frame formulation of the pel-recursive Wiener-based displacement estimation algorithm [1] is presented. The derivation of the algorithm is based on the assumption that both the so-called update of the initial estimate of the displacement vector and the linearization error are samples of stochastic processes. A linear least-squares estimate of the update of the initial estimate of the displacement vector from the previous frame to the current is provided, based on w observations in a causal window W of each of the v previous frames. The sensitivity of the pel-recursive algorithms in the areas where occlusion occurs is studied and their performance is improved with adaptive regularization of the inverse problem that is involved. Based on our experiments with typical video-conferencing scenes, we concluded that the multiple frame Wiener-based algorithm performs better than the two-frame Wiener-based pel-recursive algorithm with respect to robustness, stability, and smoothness of the velocity field.© (1989) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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