Abstract
This paper proposes a new feature extraction method for face recognition. The proposed method is based on Local Feature Analysis (LFA). LFA is known as a local method for face recognition since it constructs kernels which detect local structures of a face. It, however, addresses only image representation and has a problem for recognition. In the paper, we point out the problem of LFA and propose a new feature extraction method by modifying LFA. Our method consists of three steps. After extracting local structures using LFA, we construct a subset of kernels, which is efficient for recognition. Then we combine the local structures to represent them in a more compact form. This results in new bases which have compromised aspects between kernels of LFA and eigenfaces for face images. Through face recognition experiments, we verify the efficiency of our method.
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© 2005 Springer-Verlag Berlin Heidelberg
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Lee, Y., Lee, K., Pan, S. (2005). Local and Global Feature Extraction for Face Recognition. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_23
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DOI: https://doi.org/10.1007/11527923_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27887-0
Online ISBN: 978-3-540-31638-1
eBook Packages: Computer ScienceComputer Science (R0)