3D object decomposition and super resolution
Syed Altaf Ganihar, Shreyas Joshi, Shankar Gangisetty, Uma Mudenagudi · 2014
In this paper we propose to address the problem of 3D object decomposition and super resolution. We model the 3D object as a set of Riemannian manifolds and propose metric tensor and Christoffel symbols as a novel set of features for 3D object decomposition using polynomial kernel SVM classifier. The super resolution of the 3D point clouds is carried out using the decomposed object by using selective interpolation techniques. The effectiveness of the proposed framework is demonstrated on 3D objects obtained from different datasets and achieve comparable results.