Based on Local Feature Region Fusion of Facial Expression Recognition

摘要：

A facial expression recognition method based on the fuzzy information fusion of the local features is proposed.Each original image is divided into many sub-images and all training sub-images from the same position construct a new training subset The traditional PCA (principal component analysis) operates directly on a set of new training subsets respectively and a set of projection sub-spaces can be obtained.The local sub-feature of an unknown face can be extracted by projecting each sub-image onto the corresponding sub-space.According to these local sub-features,the membership grades of the test subimages to the training sub-images can be determined.The identity of an unknown facial expression image is determined by the fuzzy fusion which aggregates the local sub-features.The experiments on JAFFE database show the effectiveness of the proposed method.

关键词： facial expression recognition principal component analysis (PCA) fusion local feature region

作者: Chuan Wan Yantao Tian Hongwei Chen Shuaishi Liu

作者单位: School of Communication Engineering Jilin University Changchun,China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 202-206

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）