Geodesic Distance on Riemannian Manifold using Jacobi Iterations in 3D Face Recognition System

Rachid Ahdid (Sultan Moulay Slimane University)
Said Safi (Sultan Moulay Slimane University)
Mohamed Fakir (Sultan Moulay Slimane University)
Bouzid Manaut (Sultan Moulay Slimane University)

International Journal of Informatics and Communication Technology (IJ-ICT)
Vol 6, No 1: April 2017

In this paper, we present an automatic application of 3D face recognition system using geodesic distance in Riemannian geometry. We consider, in this approach, the three dimensional face images as residing in Riemannian manifold and we compute the geodesic distance using the Jacobi iterations as a solution of the Eikonal equation. The problem of solving the Eikonal equation, unstructured simplified meshes of 3D face surface, such as tetrahedral and triangles are important for accurately modeling material interfaces and curved domains, which are approximations to curved surfaces in R3. In the classifying steps, we use: Neural Networks (NN), K-Nearest Neighbor (KNN) and Support Vector Machines (SVM). To test this method and evaluate its performance, a simulation series of experiments were performed on 3D Shape REtrieval Contest 2008 database (SHREC2008).