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Method and system for face recognition using deep collaborative representation-based classification

机译:使用基于深度协作表示的分类的人脸识别方法和系统

摘要

The present invention provides a face recognition method. The method includes obtaining a plurality of training face images which belongs to a plurality of face classes and obtaining a plurality of training dictionaries corresponding to the training face images. A face class includes one or more training face images. The training dictionaries include a plurality of deep feature matrices. The method further includes obtaining an input face image. The input face image is partitioned into a plurality of blocks, whose corresponding deep feature vectors are extracted using a deep learning network. A collaborative representation model is applied to represent the deep feature vectors with the training dictionaries and representation vectors. A summation of errors for all blocks corresponding to a face class is computed as a residual error for the face class. The input face image is classified by selecting the face class that yields a minimum residual error.
机译:本发明提供了一种面部识别方法。该方法包括获得属于多个面部类别的多个训练面部图像,以及获得与训练面部图像相对应的多个训练词典。脸部类别包含一个或多个训练脸部图像。训练词典包括多个深度特征矩阵。该方法还包括获得输入面部图像。将输入的面部图像划分为多个块,使用深度学习网络提取其相应的深度特征向量。应用协作表示模型以训练字典和表示向量表示深度特征向量。计算对应于面部类别的所有块的误差总和作为面部类别的残留误差。通过选择产生最小残留误差的面部类别对输入的面部图像进行分类。

著录项

  • 公开/公告号US9430697B1

    专利类型

  • 公开/公告日2016-08-30

    原文格式PDF

  • 申请/专利权人 TCL RESEARCH AMERICA INC.;

    申请/专利号US201514791388

  • 申请日2015-07-03

  • 分类号G06K9;G06K9/66;G06K9/46;G06F17/30;G06T7;

  • 国家 US

  • 入库时间 2022-08-21 14:29:48

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