Abstract
The algorithmic techniques for the implementation of the Linear Discriminant Analysis (LDA) play an important role when the LDA is applied to the high dimensional pattern recognition problem such as face recognition or verification. The LDA implementation in the context of face recognition and verification is investigated in this paper. Three main algorithmic techniques: matrix transformation, the Cholesky factorisation and QR algorithm, the Kronecker canonical form and QZ algorithm are proposed and tested on four publicly available face databases (M2VTS, YALE, XM2FDB, HARVARD)1. Extensive experimental results support the conclusion that the implementation based on the Kronecker canonical form and the QZ algorithm accomplishes the best performance in all experiments
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Li, Y., Kittler, J., Matas, J. (1999). Effective Implementation of Linear Discriminant Analysis for Face Recognition and Verification. In: Solina, F., Leonardis, A. (eds) Computer Analysis of Images and Patterns. CAIP 1999. Lecture Notes in Computer Science, vol 1689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48375-6_29
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DOI: https://doi.org/10.1007/3-540-48375-6_29
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