Enhanced maximum likelihood face recognition
暂无分享,去创建一个
A method to enhance maximum likelihood face recognition is presented. It selects a more robust weighting parameter and discards unreliable dimensions to circumvent problems of the unreliable small and zero eigenvalues. This alleviates the over-fitting problem in face recognition, where the high dimensionality and limited number of training samples are critical issues. The proposed method gives superior experimental results.
[1] Alex Pentland,et al. Bayesian face recognition , 2000, Pattern Recognit..
[2] Hakan Cevikalp,et al. Discriminative common vectors for face recognition , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] Baback Moghaddam,et al. Principal Manifolds and Probabilistic Subspaces for Visual Recognition , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Hyeonjoon Moon,et al. The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..