基于面部区域的面部表情识别

Khadija Lekdioui, Y. Ruichek, R. Messoussi, Youness Chaabi, R. Touahni
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引用次数: 23

摘要

提出了一种基于人脸分解的人脸表情识别方法。首先,利用IntraFace算法检测到的面部特征提取7个感兴趣区域(ROI),分别代表人脸的主要组成部分(左眉、右眉、左眼、右眼、眉间、鼻口);然后,使用LBP、CLBP、LTP和Dynamic LTP等不同的局部描述符提取特征。最后,将代表人脸图像的特征向量输入到多类支持向量机中,完成人脸识别任务。在两个公开数据集上的实验结果表明,该方法优于其他基于人脸分解的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Facial expression recognition using face-regions
This paper proposes a facial expression recognition method based on a novel facial decomposition. First, seven regions of interest (ROI), representing the main components of face (left eyebrow, right eyebrow, left eye, right eye, between eyebrows, nose and mouth), are extracted using facial landmarks detected by IntraFace algorithm. Then, different local descriptors, such as LBP, CLBP, LTP and Dynamic LTP, are used to extract features. Finally, feature vector, representing face image, is fed into a multiclass support vector machine to achieve the recognition task. Experimental results on two public datasets show that the proposed method outperforms state of the art methods based on other facial decompositions.
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