@inproceedings{af245b00e83e4f36865e1347a1abf268,
title = "A SVM face recognition method based on optimized gabor features",
abstract = "A novel Support Vector Machine (SVM) face recognition method using optimized Gabor features is presented in this paper. 200 Gabor features are first selected by a boosting algorithm, which are then combined with SVM to build a two-class based face recognition system. While computation and memory cost of the Gabor feature extraction process has been significantly reduced, our method has achieved the same accuracy as a Gabor feature and Linear Discriminant Analysis (LDA) based multi-class system.",
keywords = "Gabor features, Linear discriminant analysis, Support vector machine",
author = "Linlin Shen and Li Bai and Zhen Ji",
year = "2007",
doi = "10.1007/978-3-540-76414-4_17",
language = "English",
isbn = "9783540764137",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "165--174",
booktitle = "Advances in Visual Information Systems - 9th International Conference, VISUAL 2007, Revised Selected Papers",
address = "Germany",
note = "9th International Conference on Visual Information Systems, VISUAL 2007 ; Conference date: 28-06-2007 Through 29-06-2007",
}