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.
Abstract (translated)
本文将基于测地距离的递推滤波器应用于稀疏数据插值问题。该方法具有通用性强、易于应用于各种稀疏数据的特点。在定性和定量评价的三个实验中，我们证明了与其他插值技术相比的优越性。
URL
https://arxiv.org/abs/1905.02229
