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Face recognition using elastic local reconstruction based on a single face image

机译:基于单个人脸图像的弹性局部重建人脸识别

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In this paper, we propose a new face recognition algorithm based on a single frontal-view image for each face subject, which considers the effect of the face manifold structure. To compare two near-frontal face images, each face is considered a combination of a sequence of local image blocks. Each of the image blocks of one image can be reconstructed according to the corresponding local image block of the other face image. Then an elastic local reconstruction (ELR) method is proposed to measure the similarities between the image block pairs in order to measure the difference between the two face images. Our algorithm not only benefits from the face manifold structure, in terms of being robust to various image variations, but also is computationally simple because there is no need to build the face manifold. We evaluate the performance of our proposed face recognition algorithm with the use of different databases, which are produced under various conditions, e.g. lightings, expressions, perspectives, with/without glasses and occlusions. Consistent and promising experimental results were obtained, which show that our algorithm can greatly improve the recognition rates under all the different conditions. (C) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
机译:在本文中,我们提出了一种新的基于每个人脸主题的正面图像的人脸识别算法,其中考虑了人脸流形结构的影响。为了比较两个近正面的面部图像,每个面部被认为是一系列局部图像块的组合。一个图像的每个图像块可以根据另一张面部图像的相应局部图像块进行重建。然后提出了一种弹性局部重建(ELR)方法来测量图像块对之间的相似度,以测量两个面部图像之间的差异。我们的算法不仅在面对各种图像变化的鲁棒性方面受益于脸部歧管结构,而且由于无需构建脸部歧管而在计算上也很简单。我们使用在不同条件下产生的不同数据库来评估我们提出的面部识别算法的性能。照明,表情,观点,戴/不戴眼镜和遮挡物。获得了一致且有希望的实验结果,表明我们的算法可以在所有不同条件下大大提高识别率。 (C)2007模式识别学会。由Elsevier Ltd.出版。保留所有权利。

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