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- W1601714215 abstract "Face recognition presents the difficulty of occlusion. The occlusion is generally endowed a little weight to weaken its influence on recognition performance. On the basis of this idea, many existing algorithms used the reconstruction error or projection error as the probability estimation for occlusion image. These methods require iterative computation, which may lead to the difficulty of threshold selection and high time complexity. To solve these problems, this paper proposed a novel method for occlusion face recognition by using an error detection method. First, a face image is divided into four regions and we extract feature and detect error for each region. Second, we use the logarithmic transform error operator to calculate the weight value of each region. The experiments based on the AR database demonstrate that the proposed algorithm for occlusion face recognition achieves high efficiency and good robustness and outperforms the existing methods for certain occlusion recognition." @default.
- W1601714215 created "2016-06-24" @default.
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- W1601714215 date "2015-06-01" @default.
- W1601714215 modified "2023-09-24" @default.
- W1601714215 title "Face recognition based on error detection under partial occlusion" @default.
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- W1601714215 doi "https://doi.org/10.1109/icsssm.2015.7170323" @default.
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