Database size effects on performance on a smart card face verification system

T. Bourlai, J. Kittler, K. Messer
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引用次数: 7

Abstract

We study the effect of development set size on system performance, as measured by verification error. The study was performed using the FERET and FRGC2 databases to construct development training sets of varying size, while XM2VTS was used to test the system. Surprisingly, the achievable performance levels off relatively quickly. Increasing the size of the development set does not bring any benefit. On the contrary it may result in performance degradation. This finding appears to be development set independent. However, the choice of the development set size is protocol dependent
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数据库大小对智能卡人脸验证系统性能的影响
我们通过验证误差来研究开发集大小对系统性能的影响。研究使用FERET和FRGC2数据库构建不同大小的开发训练集,同时使用XM2VTS对系统进行测试。令人惊讶的是,可实现的性能相对较快地趋于稳定。增加开发集的大小不会带来任何好处。相反,它可能导致性能下降。这一发现似乎与发育集无关。但是,开发集大小的选择取决于协议
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