• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International symposium on multispectral image processing and pattern recognition >Facial expression recognition based on weber local descriptor and sparse representation
【24h】

Facial expression recognition based on weber local descriptor and sparse representation

机译：基于Weber局部描述符和稀疏表示的面部表情识别

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

摘要

Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.
机译：自动面部表情识别已成为近十年来计算机视觉领域的研究热点之一。在过去的十年中，已经提出了许多最先进的方法，这些方法可以基于面部图像执行非常高的准确率，而不会受到任何干扰。如今，许多研究人员开始挑战对具有腐败和遮挡的面部表情图像进行分类的任务，基于稀疏表示的分类框架已得到广泛使用，因为它可以抵抗腐败和遮挡。因此，本文提出了一种基于Weber局部描述符（WLD）和稀疏表示的面部表情识别新方法。该方法包括三个部分：首先将面部图像分为多个局部斑块，然后提取每个斑块的WLD直方图，最后将所有WLD直方图特征组合成矢量，并与SRC组合以对面部表情进行分类。在Cohn-Kanade数据库上的实验结果表明，该方法对遮挡和破坏具有鲁棒性。

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