2011/10/25 by Thái Hoàng Lê, Thai Hoang Le, Le, Thai Hoang +2
Computer Science · Earth and Planetary Sciences · Engineering · #Advanced Algorithms and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face and Expression Recognition #Remote Sensing and Land Use #cs.CV
paper · pdf · doi:10.48550/arxiv.1110.5404
10 pages, 7 figures, 2 tables, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 4, No. 3, September, 2011
arxiv created 2011/10/25 · openalex publication_date 2011/10/25 · arxiv updated 2011/10/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The paper will present a novel approach for solving face recognition problem. Our method combines 2D Principal Component Analysis (2DPCA), one of the prominent methods for extracting feature vectors, and Support Vector Machine (SVM), the most powerful discriminative method for classification. Experiments based on proposed method have been conducted on two public data sets FERET and AT&T; the results show that the proposed method could improve the classification rates.