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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kayim, G. Sari, C. Akgul, C.B. |
| Copyright Year | 2013 |
| Description | Author affiliation: Vistek ISRA Vision, Bogazici Univ., Istanbul, Turkey (Kayim, G.; Sari, C.; Akgul, C.B.) |
| Abstract | In this work, we primarily aim at estimating the performance of SVM-based gender recognition using widely used DCT and LBP facial features, as faithful as possible. The SVM classifier has been trained and cross-validated on the FERET database containing 2720 instances, while for testing, the LFW database containing over 13000 instances has been used. We have observed that the over 95% cross-validation performance on FERET is overly optimistic as compared to the true test performance of %78 on LFW. Additionally, we have used random decision forests as a discriminative feature selection scheme and we have shown that similar performance can be maintained while reducing the original number of features significantly. As a by-product, the scheme can also be used to localize the most discriminative facial gender features. |
| Sponsorship | IEEE Turkey Sect. SP Chapter |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 263872 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467355629 |
| e-ISBN | 9781467355636 |
| e-ISBN | 9781467355612 |
| DOI | 10.1109/SIU.2013.6531267 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-04-24 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Databases Face recognition dct Resource description framework svm lbp Discrete cosine transforms Facial features feature selection gender recognition pattern recognition |
| Content Type | Text |
| Resource Type | Article |
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