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FisherFace

于 2013-03-19 发布 文件大小:3443KB
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  Fisherface方法的实现是在PCA数据重构的基础上完成的,首先利用PCA将高维数据投影到低维特征脸子空间,然后再在这个低维特征脸子空间上用LDA特征提取方法得到Fisherface。程序中使用参数寻优的方法来寻找最佳投影维数,以达到比较理想的识别效果。 (The Fisherface method implemented in the PCA data reconstruction based on the completion of the first use of PCA projection of high-dimensional data to a low dimensional feature subspace, and then on the characteristics of low-dimensional subspace LDA feature extraction methods to get the Fisherface. Program parameter optimization method is used to find the best projection dimension, in order to achieve the ideal identification.)

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