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A study of features and classifiers for multiple environment face recognition system

机译:多种环境面部识别系统的特征和分类研究

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This paper presents a study of multiple environment consideration for face recognition system in order to investigate the suitable pairs of features and classifiers of the system. The variation of the environment is devoted to the consideration for illumination of the working system and poses of the users. The images used in the dataset were prescribed as grayscale in 2D images. The performances of selected features were evaluated for each classifier. The experiments were designed in two main situations consisting of similar illumination setting for both training set and testing set, and different illumination of both sets. The experimental results demonstrate that the similarity in lighting of training set and testing set provides better accuracy than that from where the illumination settings between training set and testing set are different.
机译:本文介绍了对面部识别系统的多种环境考虑因素的研究,以研究系统的合适特征和分类器。环境的变化致考虑了工作系统的照明和用户的姿势。 DataSet中使用的图像在2D图像中规定为灰度。为每个分类器评估所选特征的性能。实验是在两个主要情况下设计的,该主要情况包括训练集和测试集的相似照明设置,以及两组的不同照明。实验结果表明,训练集和测试集的照明中的相似性提供了比训练集和测试集之间的照明设置不同的更好的准确性。

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