Abstract
This paper introduces an improved-LDA (I-LDA) approach to face recognition, which can effectively deal with the two problems encountered in LDA-based face recognition approaches: 1) the degenerated generalization ability caused by the “small sample size” problem, and 2) Fisher criterion is nonoptimal with respect to classification rate. In particular, the I-LDA approach can also improve the classification rate of one or several appointed classes by using a suitable weighted scheme. The key to this approach is to use the direct-LDA techniques for dimension reduction and meanwhile utilize a modified Fisher criterion that it is more closely related to classification error. Comparative experiments on ORL face database verify the effectiveness of the proposed method.
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© 2004 Springer-Verlag Berlin Heidelberg
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Zhou, D., Yang, X. (2004). Face Recognition Using Improved-LDA. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_84
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DOI: https://doi.org/10.1007/978-3-540-30126-4_84
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23240-7
Online ISBN: 978-3-540-30126-4
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