AAM-based Face Shape Classification Method Used for Facial Expression Recognition
AAM-based Face Shape Classification Method Used for Facial Expression Recognition
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发表时间：
2013
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通讯作者：
Lu Li;Jaehun Soo;Hyun-Chool Shin;Youngjoon Han
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作者：
Lu Li;Jaehun Soo;Hyun-Chool Shin;Youngjoon Han
面部表情识别是人机交流的关键要素。然而，身份、性别、脸型等噪声会严重影响多人的表情识别。本文提出了一种基于aam的人脸形状噪声去除方法，以提高人脸表情识别性能。首先，利用主动外观模型（AAM）提取人脸特征，该特征以形状参数的形式包含丰富的人脸几何信息；随后，基于AAM的形状参数，提出了一种基于支持向量机的人脸分类方法，对瓜子、圆形和方形三种主要人脸形状进行分类。最后，提出了一种基于脸型分类的人脸表情识别方法，提高了人脸表情的识别率。
— Facial expression recognition is a key element in human-computer communication. However, some noises such as identity, gender and face shape may seriously have an effect on multi-person's expression recognition. In this paper, an AAM-based method is proposed to remove face shape noise for the purpose of improving facial expression recognition performance. Firstly, Active Appearance Model (AAM) is used to extract the facial feature, which includes abundant face geometry information in the form of shape parameters. Subsequently, based on the shape parameters of AAM, an SVM-based classification method is proposed to classify the main face shape--melon seed, round and square. Finally, a proposal for facial expression recognition using face shape classification is given, which can improve the recognition rate.