...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Computers >Contextual Patch Feature Learning for Face Recognition
【24h】

Contextual Patch Feature Learning for Face Recognition

机译：用于人脸识别的上下文补丁特征学习

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Local features, such as local binary patterns (LBP), have shown better performance than global feature in the problem of face recognition. However, the methods to extract the local features are usually given as fixed, and also neglect the class labels of the training samples. In this paper, we propose a novel algorithm to learn a discriminate local feature from the small patches of the face image to boost the face recognition. The pixels of each image patch and its neighboring patches are both used to construct the local feature. The pixel vector of each patch is mapped to new subspaces by a transformation matrix, and mapped pixel vectors the neighboring patches are also combined to obtain the local feature vector. The subspace mapping parameter and the neighboring patch combination parameter are learned to minimize the distances of local features between the same person, and at the same time to maximize that between different persons. We perform experiments on some benchmark face image database to show the advantage of the proposed method.
机译：在人脸识别问题上，局部特征（例如局部二进制模式（LBP））显示出比全局特征更好的性能。但是，提取局部特征的方法通常是固定的，并且也忽略了训练样本的类别标签。在本文中，我们提出了一种新颖的算法来从人脸图像的小补丁中学习区分局部特征，以增强人脸识别能力。每个图像补丁及其相邻补丁的像素都用于构造局部特征。每个斑块的像素矢量通过变换矩阵映射到新的子空间，并且相邻斑块的映射像素矢量也被组合以获得局部特征矢量。学习子空间映射参数和相邻补丁组合参数以最小化同一个人之间的局部特征的距离，并且同时最大化不同个人之间的局部特征的距离。我们在一些基准人脸图像数据库上进行了实验，以证明该方法的优势。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号