Abstract: 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.

Key words: facial expression recognition, sub-region weighting, different age groups