Three Dimensional Face Surface Recognition by Geodesic Distance Using Jacobi Iterations
| Autor: | Said Said, Mohamed Fakir, Khaddouj Taifi, Rachid Ahdid, Youssef Ouadid, Bouzid Manaut |
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| Rok vydání: | 2017 |
| Předmět: |
Geodesic
Computer science Eikonal equation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 010103 numerical & computational mathematics 02 engineering and technology Riemannian geometry Riemannian manifold Surface (topology) 01 natural sciences Facial recognition system symbols.namesake Face (geometry) 0202 electrical engineering electronic engineering information engineering symbols 020201 artificial intelligence & image processing Polygon mesh 0101 mathematics Algorithm ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | 2017 14th International Conference on Computer Graphics, Imaging and Visualization. |
| DOI: | 10.1109/cgiv.2017.28 |
| Popis: | 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 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). |
| Databáze: | OpenAIRE |
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