A hybrid local feature for face recognition

Authors:
Gaopeng Gou;Di Huang;Yunhong Wang
Affiliations:
Laboratory of Intelligent Recognition and Image Processing, Beijing Key Laboratory of Digital Media, Beihang University, Beijing, China;Laboratory of Intelligent Recognition and Image Processing, Beijing Key Laboratory of Digital Media, Beihang University, Beijing, China;Laboratory of Intelligent Recognition and Image Processing, Beijing Key Laboratory of Digital Media, Beihang University, Beijing, China
Venue:
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Year:
2012

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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.