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http://dx.doi.org/10.3745/JIPS.02.0037

Evaluation of Histograms Local Features and Dimensionality Reduction for 3D Face Verification  

Ammar, Chouchane (Dept. of Electrical Engineering, University of Mohamed Khider)
Mebarka, Belahcene (Dept. of Electrical Engineering, University of Mohamed Khider)
Abdelmalik, Ouamane (Centre de Developpement des Technologies Avancees)
Salah, Bourennane (Institut Fresnel, UMR CNRS 7249, Ecole Centrale Marseille)
Publication Information
Journal of Information Processing Systems / v.12, no.3, 2016 , pp. 468-488 More about this Journal
Abstract
The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.
Keywords
3D Face Verification; Depth Image; Dimensionality Reduction; Histograms Local Features; Local Descriptors; Support Vector Machine;
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