Is ICA significantly better than PCA for face recognition?
Is ICA significantly better than PCA for face recognition?
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DOI：
10.1109/iccv.2005.127
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发表时间：
2005-10
期刊：
影响因子：
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通讯作者：
Jian Yang;David Zhang;Jing-yu Yang
中科院分区：
文献类型：
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作者：
Jian Yang;David Zhang;Jing-yu Yang
在以往的研究中，标准主成分分析（PCA）一直被用作评价ICA人脸识别系统的基线算法。在本文中，我们研究了伊卡的两种架构的图像表示，并发现伊卡架构I涉及的PCA过程中的垂直中心（PCA I），而伊卡架构II涉及的白化PCA过程中的水平中心（PCA II）。因此，将这两种PCA算法作为基准算法来重新评估基于ICA的人脸识别系统是合理的。实验在FERET人脸数据库上进行。实验结果表明，伊卡架构I（II）和PCA I（II）之间没有显着的性能差异，虽然伊卡架构II显着优于标准PCA。可以得出结论，伊卡的性能强烈依赖于其所涉及的PCA过程。单纯的伊卡投影对人脸识别的性能影响不大。
The standard PCA was always used as baseline algorithm to evaluate ICA-based face recognition systems in the previous research. In this paper, we examine the two architectures of ICA for image representation and find that ICA architecture I involves a PCA process by vertically centering (PCA I), while ICA architecture II involves a whitened PCA process by horizontally centering (PCA II). So, it is reasonable to use these two PCA versions as baseline algorithms to revaluate the ICA-based face recognition systems. The experiments were performed on the FERET face database. The experimental results show there is no significant performance differences between ICA architecture I (II) and PCA I (II), although ICA architecture II significantly outperforms the standard PCA. It can be concluded that the performance of ICA strongly depends on its involved PCA process. The pure ICA projection has little effect on the performance of face recognition.