Feature Extraction Methods for Real-Time Face Detection and Classification
<p/> <p>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 nonpara...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2005-01-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1155/ASP.2005.2061 |
| Summary: | <p/> <p>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.</p> |
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| ISSN: | 1687-6172 1687-6180 |