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In this paper, we adapt the geodesic distance-based recursive filter to thesparse data interpolation problem. The proposed technique is general and can beeasily applied to any kind of sparse data. We demonstrate the superiority overother interpolation techniques in three experiments for qualitative andquantitative evaluation.  In addition, we compare our method with the popular interpolation algorithmpresented in the EpicFlow optical flow paper that is intuitively motivated by asimilar geodesic distance principle. The comparison shows that our algorithm ismore accurate and considerably faster than the EpicFlow interpolationtechnique.

Sparse data interpolation using the geodesic distance affinity space