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人脸检测和表情识别的动态链接库，并且含有C++调用的例子，非常适合研究人脸识别和表情识别！-face detection and expression recognition of the dynamic link library, called C and contain examples very suitable for the study face recognition and facial recognition!
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不错的“日本人脸表情库”，做人脸识别的人会用的到。-Good "Japanese facial expression database," so people will use face recognition to。
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摘 要： 提出了一种基于改进 Ha u s d o r f f距离的人脸相似度匹配的方法， 该方法首先将人脸划分为脸型、 双眼、 鼻、 嘴等几个特征点
集， 分别计算各部分的改进 Ha u s d o r f f 距离， 然后进行加权计算相似度。利用该方法， 在 A S M( 主动形状模型) 定位人脸的基础上进
行了人脸检索。 实验表明， 利用人脸相似度计算方法对人脸特征库进行搜索， 达到 了较好的效果。同时结合 A S M 自动人脸检测， 本
方法可以全自动完成人脸匹配， 应
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基于小波变换和弹性图识别的人脸表情识别论文-The Human Facial Combined Expression Recognition System
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近年来，面部识别技术已经备受关注，其研究已迅速，因为它有许多在计算机视觉通讯和控制系统，自动存取的应用潜力。特别是，人脸检测是一种面部识别作为自动人脸识别第一步的重要组成部分。
然而，人脸检测并不简单，因为它需要用到许多技术，如构成变化（前，非前），闭塞，形象定位，照明条件和面部表情的变化-In recent years, face recognition technology has been concern that its research has rapidly because it
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三维人脸识别的经典文章，是三维人脸表情识别引用极多的经典文章-The Painful Face – Pain Expression Recognition Using Active Appearance Models
Active Appearance Models, Support Vector Machines, Pain,
Facial expression, Automatic facial image analysis
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aleix@ecn.
Semantic queries to a database of images are more
desirable than low-level feature queries, because they
facilitate the user s task. One such approach is the
object-related image retrieval. In the context
people s names and facia
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facilitate the user s task. One such approach is the
object-related image retrieval. In the context of face
images, it is of interest to retrieve images based on
people s names and facial expressions. However, when
images of the database a
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用特征脸的方法来进行表情特征的提取，进而实现表情识别，对六种基本表情进行识别-With the characteristic expression of the face approach to feature extraction, thus achieving expression recognition, identification of the six basic facial expressions
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本程序用kpca，pls，svm来实现人脸识别，表情分辨效果明显，分辨率为百分之九十七-This program with kpca, PLS, SVM to achieve face recognition, the facial expression distinguish effect is obvious, the resolution is ninety-seven percent
nine percent
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本程序用kpca，pls，svm来实现人脸识别，表情分辨效果明显，分辨率为百分之九十五-This program with kpca, PLS, SVM to achieve face recognition, the facial expression distinguish effect is obvious, the resolution is ninety-five percent
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本程序用kpca，pls，svm来实现人脸识别，表情分辨效果明显，分辨率为百分之九十四-This program with kpca, PLS, SVM to achieve face recognition, the facial expression distinguish effect is obvious, the resolution is ninety-four percent
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This program with kpca, PLS, SVM to achieve face recognition, the facial expression distinguish effect is obvious, the resolution is ninety-four percent
-This program with kpca, PLS, SVM to achieve face recognition, the facial expression distinguis
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利用tensorflow建立以个用于面部表情识别的模型(Using tensorflow to build a model for facial expression recognition)
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表情识别，可以识别出物种表情，包括平静 哭泣 开心 惊讶等的表情识别(Expression recognition can identify facial expressions, including expression recognition, such as calm crying, happy surprise, and so on.)
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FER2013 facial expression recognition data set greater than 30000 images
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基于matlab的人脸表情识别，LBP+LPQ算法融合(Facial expression recognition based on MATLAB)
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利用dlib数据库和serial port进行表情识别，此为上位机dlib部分，串口需要请留言(Using Dlib database and serial port to do facial expression recognition, this is Dlib part of host computer. Serial port needs to leave message.)
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opencv源代码表情识别，可以进行简单的表情识别(The opencv expression recognition code written abroad, can do simple facial expression recognition.)
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基于特征脸的人脸表情识别matlab代码(Facial expression recognition matlab code based on feature face)
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