Robust Design of Face Recognition Systems

机译：人脸识别系统的稳健设计

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Currently, most face recognition methods provide a number of parameters to be optimized, leaving the selection and optimization of the right parameter set is necessary for the implementation. The choice of the right parameter set that is suitable for a rich enough class of input faces in pose and illumination variations is, however, quite difficult. We propose robust parameter estimation, using the Taguchi method, when applied to 2nd order mixture of eigenfaces method that allows effective (near optimal) performance under pose and illumination variations. A number of experimental results confirm the improvement (via robustness) vis-'a-vis conventional parameter estimation methods, and these methods promise a solution to the design of efficient parameter sets that support many multi-variable face recognition systems.

机译：当前，大多数人脸识别方法提供了许多要优化的参数，而对于实现而言，必须选择和优化正确的参数集。然而，选择合适的参数集以适应姿势和照明变化中足够丰富的输入面部非常困难。我们提出了使用Taguchi方法的鲁棒参数估计方法，该方法应用于本征面方法的2阶混合时，可以在姿势和光照变化下实现有效（近乎最佳）性能。大量实验结果证实了相对于常规参数估计方法的改进（通过鲁棒性），这些方法有望为支持许多多变量面部识别系统的有效参数集设计提供一种解决方案。

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来源
《International Conference on Computational Science and Its Applications(ICCSA 2006) pt.2; 20060508-11; Glasgow(GB)》|2006年|P.96-105|共10页
会议地点 Glasgow(GB)
作者
Sunjin Yu; Hyobin Lee; Jaihie Kim; Sangyoun Lee;
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作者单位

Graduate Program in Biometrics, and of BERC, Yonsei University, 134, Sinchon-dong Seodaemun-gu, Seoul 120-749, Korea;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
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Robust Design of Face Recognition Systems

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