We propose Independent Component Analysis representation and Support Vector Machine classification to extract facial features in a face detection/localization context. The goal is to find a better space where project the data in order to build ten different face-feature classifiers that are robust to illumination variations and bad environment conditions. The method was tested on the BANCA database, in different scenarios: controlled conditions, degraded conditions and adverse conditions. © Springer-Verlag 2003.
CITATION STYLE
Antonini, G., Popovici, V., & Thiran, J. P. (2003). Independent component analysis and support vector machine for face feature extraction. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2688, 111–118. https://doi.org/10.1007/3-540-44887-x_14
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