摘要
为了提高人脸表情识别的识别率,提出一种LBP和SVM决策树相结合的人脸表情识别算法。首先利用LBP算法将人脸表情图像转换为LBP特征谱,然后将LBP特征谱转换成LBP直方图特征序列,最后通过SVM决策树算法完成人脸表情的分类和识别,并且在JAFFE人脸表情库的识别中证明该算法的有效性。
In order to improve the recognition rate of facial expression, proposes a facial expression recognition algorithm based on a LBP and SVM decision tree. First facial expression image is converted to LBP characteristic spectrum using LBP algorithm, and then the LBP character-istic spectrum into LBP histogram feature sequence, finally completes the classification and recognition of facial expression by SVM deci-sion tree algorithm, and proves the effectiveness of the proposed method in the recognition of facial expression database in JAFFE.
出处
《现代计算机》
2014年第6期40-44,共5页
Modern Computer
关键词
表情识别
SVM决策树
直方图序列
LBP
Facial Expression Recognition
LBP
SVM Decision Tree
Histogram
