Abstract
We propose a complete scheme for face detection and recognition. We have used a Bayesian classifier for face detection and a nearest neighbor approach for face classification. To improve the performance of the classifier, a feature extraction algorithm based on a modified nonparametric discriminant analysis has also been implemented. The complete scheme has been tested in a real-time environment achieving encouraging results. We also show a new boosting scheme based on adapting the features to the misclassified examples, achieving also interesting results.
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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Masip, D., Bressan, M. & Vitrià, J. Feature Extraction Methods for Real-Time Face Detection and Classification. EURASIP J. Adv. Signal Process. 2005, 531492 (2005). https://doi.org/10.1155/ASP.2005.2061
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DOI: https://doi.org/10.1155/ASP.2005.2061