• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Information Science and Control Engineering >Facial Expression Recognition Algorithm Based on Reverse Co-Salient Regions (RCSR) Features
【24h】

Facial Expression Recognition Algorithm Based on Reverse Co-Salient Regions (RCSR) Features

机译：基于反向共凸区域特征的人脸表情识别算法

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

摘要

To solve the problems of absence of expression-correlation in single-image-based expression recognition, and limitation of one classifier, a novel facial expression recognition method based on reverse co-saliency region features is proposed in this paper. Firstly, seven different classifications of expression images of a same person are used to extract facial changed regions of different expressions by a reverse co-saliency features method, named Reverse Co-Salient Regions (RCSR). Secondly, the extracted salient regions are described as texture and shape features LBP and HOG. Finally, based on RCSR features, multi-classifiers decision mechanism is used for expressions recognition. The following experimental results show that the recognition accuracy increases obviously compared with 3 different kinds of single-image-based expression recognition methods.
机译：为解决基于单图像的表情识别中缺乏表情相关性和一个分类器的局限性的问题，提出了一种基于反向共显性区域特征的面部表情识别新方法。首先，使用同一人的七种不同分类的表情图像，通过反向共凸特征方法（RCSR）提取不同表情的面部变化区域。其次，将提取的显着区域描述为纹理和形状特征LBP和HOG。最后，基于RCSR特征，使用多分类器决策机制进行表情识别。以下实验结果表明，与3种不同的基于单图像的表情识别方法相比，识别精度明显提高。

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