基于子区域加权的不同年龄段人脸表情识别

人脸图像中不同子区域对表情识别的贡献度不同，而且同一子区域对不同年龄段人(如中老年、青年、儿童)的表情识别贡献度也不同。因此，若采用单一固定的子区域加权模式进行人脸表情识别，无法达到最佳识别率。为了提高识别率，提出一种可变加权值的表情识别方法。对中老年人、青年人和儿童分别建立表情数据库，分割出纯人脸区域、眼睛区域和嘴巴区域。对这些区域提取特征后将其进行加权融合，通过设置不同的权值研究其对不同年龄段人脸表情识别的影响。实验结果表明，采用可变加权值比采用固定加权值方法的识别率明显更高。对中老年人的表情识别率提高了8.6%,对青年人的表情识别率提高了4.8%,对儿童的表情识别率提高了1.4%。

Facial expression recognition of different agegroups based on face sub-region weighting

Different sub-regions in a face image contribute differently to human face expression recognition, and meanwhile one sub-region contributes differently to expression recognition for people of different ages, such as the old and the middle-aged, the young and children. Therefore, the best recognition rate may not be achieved if a fixed sub-region weighting mode is used for facial expression recognition. To improve the recognition rate, an expression recognition method with variable weight is proposed. Firstly, expression databases for old and middle-aged people, young people and children are established respectively. Secondly, pure face region is segmented from the face image. The regions of eyes and mouth are picked up further. The features of these regions are extracted, weighted and fused. By setting different weights, their effect on ex-pression recognition of different types of people is studied. The experimental results show that the facial expression recognition method using variable weighting value has significantly higher recognition rate than the method using fixed weighting value. For images of the middle-aged and old, the young, and the children, the expression recognition rate is improved by 8.6%, 4.8%, and 1.4%, respectively.