3D Object Super Resolution using Metric Tensor and Christoffel Symbols
Syed Altaf Ganihar, Shreyas Joshi, Shankar Gangisetty, Uma Mudenagudi · 2014
In this paper we address the problem of 3D super resolution. 3D super resolution is a process of generating high resolution point cloud, given a low resolution point cloud. We model 3D object as a set of Riemannian manifolds in continuous and discretized space. We propose to use Riemannian metric tensor and Christoffel symbols as a set of features to capture the inherent geometry of the 3D object. We propose a learning framework to decompose 3D object using metric tensor and Christoffel symbols into a set of basis functions to selectively super resolve the 3D object. We demonstrate the proposed algorithm on 3D objects and achieve better results than reported in literature.