Three Dimensional Face Surfaces Analysis using Geodesic Distance

Rachid AHDID^1, , Said SAFI¹ and Bouzid MANAUT¹

¹Interdisciplinary Laboratory of Research in Sciences and Technologies (LIRST), Sultan Moulay Slimane University, Beni Mellal, Morocco

Cite this paper:
Rachid AHDID, Said SAFI and Bouzid MANAUT. Three Dimensional Face Surfaces Analysis using Geodesic Distance. Journal of Computer Sciences and Applications. 2015; 3(3):67-72. doi: 10.12691/jcsa-3-3-2

Abstract

In this paper, we present an automatic 3D face recognition system based on the computation of the geodesic distance between the reference point and the other points in the 3D face surface. To compute a geodesic distance, we use the Fast Marching algorithm for solving the Eikonal equation. For space reduction, we apply Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (LDA). Quantitative measures of similarity are obtained and then used as inputs to several classification methods. In the classifying step, 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).

Keywords:
3D face recognition geodesic distance reference point Principal Components Analysis Linear Discriminant Analysis fast marching eikonal equation

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