Sparse representation based classification (SRC) has emerged as a new paradigm for solving face recognition problems. Further research found that the main limitation of SRC is the assumption of pixel-accurate alignment between the test image and the training set. A. Wagner used a series of linear programs that iteratively minimize the sparsity of the registration error. In this paper, we propose another face registration method called three-point positioning method. Experiments show that our proposed method achieves better performance.
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机译：基于稀疏表示的分类（SRC）已经成为解决人脸识别问题的新范例。进一步的研究发现，SRC的主要局限性是假设测试图像和训练集之间的像素精确对齐。 A. Wagner使用了一系列线性程序，这些程序迭代地最小化了配准错误的稀疏性。在本文中，我们提出了另一种人脸注册方法，称为三点定位方法。实验表明，该方法具有较好的性能。
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