A combined SIFT/SURF descriptor for automatic face recognition

Ladislav Lenc; Pavel Král

doi:10.1117/12.2052804

24 December 2013 A combined SIFT/SURF descriptor for automatic face recognition

Ladislav Lenc, Pavel Král

Proceedings Volume 9067, Sixth International Conference on Machine Vision (ICMV 2013); 90672C (2013) https://doi.org/10.1117/12.2052804
Event: Sixth International Conference on Machine Vision (ICMV 13), 2013, London, United Kingdom

Abstract

This paper deals with Automatic Face Recognition (AFR). A novel approach which combines the SIFT and SURF features for the face representation is proposed. The obtained combined SIFT/SURF descriptor is then used for face comparison by the adapted Kepenekci matching method. The proposed method is evaluated on the FERET and CTK corpora. The obtained recognition rates are 98.4% and 64.6% respectively. These recognition scores show that our approach outperforms significantly all other methods on these corpora. The differences between recognition error rates of the proposed approach and the second best one are 41% and 7% in relative value respectively.

Citation Download Citation

Ladislav Lenc and Pavel Král "A combined SIFT/SURF descriptor for automatic face recognition", Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90672C (24 December 2013); https://doi.org/10.1117/12.2052804

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