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Proceedings Paper

A combined SIFT/SURF descriptor for automatic face recognition
Author(s): Ladislav Lenc; Pavel Král
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Paper 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.

Paper Details

Date Published: 24 December 2013
PDF: 6 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90672C (24 December 2013); doi: 10.1117/12.2052804
Show Author Affiliations
Ladislav Lenc, Univ. of West Bohemia (Czech Republic)
Pavel Král, Univ. of West Bohemia (Czech Republic)


Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Antanas Verikas; Jianhong Zhou, Editor(s)

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