Recognition of 3D Objects Using Heat Diffusion Equations and Random Forests

Abstract

In this paper, we present an approach to recognize 3D objects. The method is based on the heat equation by calculating the geodesic distance between any pair of points x, y on Riemannian manifold. The method is compared to the light field descriptor (LFD) and the salient views (SV) by using three classifier such as C4.5 decision tree and Random Forest. The proposed method is a set of classifier that makes the decision, referring to the votes. We evaluate the performance of the proposed approach on a very challenging task of recognizing different objects types using two databases.