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Human Face Detection and Facial Expression Identification

机译:人脸检测和面部表情鉴定

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For interactive human and computer interface (HCI) it is important that the computer understand facial expressions of human. With HCI the gap between computers and humans will reduce. The computers can interact in more appropriate way with humans by judging their expressions. There are various techniques for facial expression recognition which focuses on getting good results of human expressions. Most of these works are done on standard databases of foreign origin with six (Neutral, Happy, fear, Anger, Surprise, Sad) basic expression identification. We propose Zernike moments based feature extraction method with support vector machine to identify 8 expressions (including Disgust, and Contempt) on JAFFE and Radboud faces database with discriminative multi-manifold analysis technique with Single Sample Per person (SSPP) and finally compared results of Zernike with Hu moments.
机译:对于互动人和计算机界面(HCI),计算机理解人类的面部表情是重要的。通过HCI,计算机与人类之间的差距将减少。通过判断他们的表达,计算机可以以更合适的方式与人类交互。面部表情识别有各种技巧,专注于获得人类表达的良好结果。这些作品中的大多数都是在国外来源的标准数据库上完成,其中六个(中性,快乐,恐惧,愤怒,惊喜,悲伤)基本表达鉴定。我们提出了基于Zernike矩的特征提取方法,支持向量机,以识别Jaffe和Radboud的8个表情(包括厌恶,蔑视,蔑视)数据库,每个人(SSPP)具有单一样本的判别多流形分析技术,最后比较Zernike的结果与胡时光。

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