Sparse data interpolation using the geodesic distance affinity space
Computer Vision and Pattern Recognition
2019-05-22 v1
Abstract
In this paper, we adapt the geodesic distance-based recursive filter to the sparse data interpolation problem. The proposed technique is general and can be easily applied to any kind of sparse data. We demonstrate the superiority over other interpolation techniques in three experiments for qualitative and quantitative evaluation. In addition, we compare our method with the popular interpolation algorithm presented in the EpicFlow optical flow paper that is intuitively motivated by a similar geodesic distance principle. The comparison shows that our algorithm is more accurate and considerably faster than the EpicFlow interpolation technique.
Keywords
Cite
@article{arxiv.1905.02229,
title = {Sparse data interpolation using the geodesic distance affinity space},
author = {Mikhail G. Mozerov and Fei Yang and Joost van de Weijer},
journal= {arXiv preprint arXiv:1905.02229},
year = {2019}
}