Regularized Pel-Recursive Motion Estimation Using Generalized Cross-Validation and Spatial Adaptation
Abstract
The computation of 2-D optical flow by means of regularized pel-recursive algorithms raises a host of issues, which include the treatment of outliers, motion discontinuities and occlusion among other problems. We propose a new approach which allows us to deal with these issues within a common framework. Our approach is based on the use of a technique called Generalized Cross-Validation to estimate the best regularization scheme for a given pixel. In our model, the regularization parameter is a matrix whose entries can account for diverse sources of error. The estimation of the motion vectors takes into consideration local properties of the image following a spatially adaptive approach where each moving pixel is supposed to have its own regularization matrix. Preliminary experiments indicate that this approach provides robust estimates of the optical flow.
Cite
@article{arxiv.1611.01298,
title = {Regularized Pel-Recursive Motion Estimation Using Generalized Cross-Validation and Spatial Adaptation},
author = {Vania V. Estrela and Luis A. Rivera and Paulo C. Beggio and Ricardo T. Lopes},
journal= {arXiv preprint arXiv:1611.01298},
year = {2016}
}
Comments
8 pages, 6 figures in Proceedings of the XVI Brazilian Symposium on Computer Graphics and Image Processing, 2003. SIBGRAPI 2003. IEEE. arXiv admin note: text overlap with arXiv:1403.7365, arXiv:1611.00960