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Eigenfaces vs. Fisherfaces vs. ICA for Face Recognition;A Comparative Study

机译:特征脸,Fisherfaces与ICA的人脸识别比较研究

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Face recognition issue gained more interest recently due to its various applications and the demand of high security.Some researches with contradicting results were published concerning this issue.This paper compared three popular face recognition projection methods: (eigenfaces),(fisherfaces),and ICA.We also applied some data transformations: (Discrete Wavelet and cosine Transforms) preceding methods to see their effect.Most researches based their results on the FERET database.AR and AT&T databases were used here to see if the same results apply.We also compared the results of two sets of experiments with the second set using half the training images used in the first to observe if the results may change.Overall conclusion is it can't be stated that specific algorithm outperforms others,though ICA and Eigenfaces respectively showed better results than fisherfaces for both experiments sets and both databases.Preceding algorithms with transformations yield better results for some algorithms.
机译:人脸识别问题由于其广泛的应用和对高安全性的需求而引起了越来越多的关注。对此问题发表了一些相互矛盾的研究。本文比较了三种流行的人脸识别投影方法:(eigenfaces),(fisherfaces)和ICA。我们还应用了一些数据变换:(离散小波和余弦变换)之前的方法来观察它们的效果,大多数研究都是基于FERET数据库的结果,这里使用AR和AT&T数据库来看看是否有相同的结果,我们还进行了比较两组实验的结果,第二组实验使用第一组中使用的一半训练图像来观察结果是否可能发生变化。总体结论是,虽然ICA和Eigenfaces分别显示出更好的效果,但不能说特定算法的性能优于其他算法在两个实验集和两个数据库上的结果都比fisherfaces.preceding的算法与转换可以为某些algori产生更好的结果thms。

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