LBPH、fishface和PCA在幼儿园学生面部表情识别中的比较

Muhammad Furqan Rasyid
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引用次数: 1

摘要

人脸识别是近年来备受关注的一种生物识别技术。对快速、准确的人脸表情识别系统的需求日益增长。面部表情识别是一种用于识别某人所显示的表情的系统。一般来说,面部表情识别的研究只关注成人的面部表情。人类面部表情的引入是一个非常重要的研究领域,因为它是情感和计算机应用的融合,例如人与计算机之间的交互,压缩数据,面部动画和视频中的面部图像搜索。这个研究过程识别幼儿的面部表情,准确地说是幼儿园的学生。但在此之前,本研究系统采用了包含多种姿态和表情的个体面部的新数据库,对PCA、Fisherface和LBPH三种方法进行了比较。这将用于面部表情识别。鱼面准确率为94%,LBPH为100%,PCA为48.75%。
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Comparison Of LBPH, Fisherface, and PCA For Facial Expression Recognition of Kindergarten Student
Face recognition is the biometric personal identification that gaining a lot of attention recently. An increasing need for fast and accurate face expression recognition systems. Facial expression recognition is a system used to identify what expression is displayed by someone. In general, research on facial expression recognition only focuses on adult facial expressions. The introduction of human facial expressions is one of the very fields of research important because it is a blend of feelings and computer applications such as interactions between humans and computers, compressing data, face animation and face image search from a video. This research process recognizes facial expressions for toddlers, precisely for kindergarten students. But before making this research system Comparing three methods namely PCA, Fisherface and LBPH by adopts our new database that contains the face of individuals with a variety of pose and expression. which will be used for facial expression recognition. Fisherface accuracy was obtained at 94%, LBPH 100%, and PCA 48.75%.
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