@inproceedings{c83061aa9e7d44e6b6fc86b2e16cb2cd,
title = "Influence of wavelet frequency and orientation in an SVM-based parallel gabor PCA face verification system",
abstract = "We present a face verification system using Parallel Gabor Principal Component Analysis (PGPCA) and fusion of Support Vector Machines (SVM) scores. The algorithm has been tested on two databases: XM2VTS (frontal images with frontal or lateral illumination) and FRAV2D (frontal images with diffuse or zenithal illumination, varying poses and occlusions). Our method outperforms others when fewer PCA coefficients are kept. It also has the lowest equal error rate (EER) in experiments using frontal images with occlusions. We have also studied the influence of wavelet frequency and orientation on the EER in a one-Gabor PCA. The high frequency wavelets are able to extract more discriminant information compared to the low frequency wavelets. Moreover, as a general rule, oblique wavelets produce a lower EER compared to horizontal or vertical wavelets. Results also suggest that the optimal wavelet orientation coincides with the illumination gradient.",
keywords = "Data fusion, Face verification, Gabor wavelet, Parallel gabor principal component analysis, Support vector machine",
author = "{\'A}ngel Serrano and {De Diego}, {Isaac Mart{\'i}n} and Cristina Conde and Enrique Cabello and Linlin Sherr and Li Bai",
year = "2007",
doi = "10.1007/978-3-540-77226-2_23",
language = "English",
isbn = "9783540772255",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "219--228",
booktitle = "Intelligent Data Engineering and Automated Learning - IDEAL 2007 - 8th International Conference, Proceedings",
address = "Germany",
note = "8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007 ; Conference date: 16-12-2007 Through 19-12-2007",
}