• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of visual communication & image representation >Linear collaborative discriminant regression classification for face recognition
【24h】

Linear collaborative discriminant regression classification for face recognition

机译：线性协作判别回归分类用于人脸识别

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper proposes a novel face recognition method that improves Huang's linear discriminant regression classification (LDRC) algorithm. The original work finds a discriminant subspace by maximizing the between-class reconstruction error and minimizing the within-class reconstruction error simultaneously, where the reconstruction error is obtained using Linear Regression Classification (LRC). However, the maximization of the overall between-class reconstruction error is easily dominated by some large class-specific between-class reconstruction errors, which makes the following LRC erroneous. This paper adopts a better between-class reconstruction error measurement which is obtained using the collaborative representation instead of class-specific representation and can be regarded as the lower bound of all the class-specific between-class reconstruction errors. Therefore, the maximization of the collaborative between-class reconstruction error maximizes each class-specific between-class reconstruction and emphasizes the small class-specific between-class reconstruction errors, which is beneficial for the following LRC. Extensive experiments are conducted and the effectiveness of the proposed method is verified. (C) 2015 Elsevier Inc. All rights reserved.
机译：本文提出了一种新颖的人脸识别方法，该方法改进了Huang的线性判别回归分类（LDRC）算法。原始工作通过最大化类间重构误差并同时最小化类内重构误差来找到判别子空间，其中重构误差是使用线性回归分类（LRC）获得的。但是，总的类间重构误差的最大化很容易被某些特定于类的大类间重构误差所支配，这使得随后的LRC错误。本文采用了一种更好的类间重构误差度量，该度量是使用协作表示而不是特定类表示来获得的，并且可以视为所有特定类间重构误差的下限。因此，协作级间重构误差的最大化使每个特定于级间重构的误差最大化，并且强调了较小的特定于级间重构的误差，这对于随后的LRC是有益的。进行了广泛的实验，验证了所提方法的有效性。 （C）2015 Elsevier Inc.保留所有权利。

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