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Abstract
Efficient face encoding is an important issue in the area of face recognition. Compared to holistic features, local features have received increasing attention due to their good robustness to pose and illumination changes. In this paper, based on the histogram-based interest points and the speeded up robust features, we propose a hybrid local face feature, which provides a proper balance between the computational speed and discriminative power. Experiments on three databases demonstrate the effectiveness of the proposed method as well as its robustness to the main challenges of face recognition and even in practical environment.
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Authors and Affiliations
Laboratory of Intelligent Recognition and Image Processing, Beijing Key Laboratory of Digital Media, Beihang University, Beijing, China
Gaopeng Gou, Di Huang & Yunhong Wang
- Gaopeng Gou
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- Di Huang
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- Yunhong Wang
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Editors and Affiliations
Faculty of Environment, Society and Design, Department of Applied Computing, Lincoln University, P.O. Box 84, 7647, Christchurch, New Zealand
Patricia Anthony
School of Information Science and Technology, University of Tokyo, 7-3-1, Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan
Mitsuru Ishizuka
MIMOS Berhad, Knowledge Technology, Technology Park Malaysia,, 57000, Kuala Lumpur, Malaysia
Dickson Lukose
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Gou, G., Huang, D., Wang, Y. (2012). A Hybrid Local Feature for Face Recognition. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_8
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