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FisherFace, an algorithm based on PCA and LDA
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We propose an algorithm for facial expression recognition which can classify the given image into one of the seven basic facial expression categories (happiness, sadness, fear, surprise, anger, disgust and neutral). PCA is used for dimensionality red
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人脸表情识别是模式识别领域中一个重要的研究方向。人脸表情识别包括：从背景图像中检测人脸、图像采集、对人脸图像进行预处理、PCA提取表情特征、表情识别。-Face recognition is an important research direction in the field of pattern recognition. Face recognition is made up of the following parts: face detection from the backgrou
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基于PCA的人脸表情识别，可以辨别高兴，愤怒和厌恶三种表情。
-In this project, Eigenfaces are used to classify facial expression. It has been assumed that, facial expression can be classified into some discreet classes (like anger, happiness, disgust or sadness) whereas:
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ieee papaer based on facial expression pca based method
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基于PCA特征提取和距离哈希K近邻分布的人脸表情识别-PCA-based feature extraction and distribution of K-nearest neighbor distance hash Facial Expression Recognition
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openCV-C++代码，用PCA算法进行人脸主成分提取，并且用kNN算法进行实时表情识别。程序可以自己建立数据库并且进行识别，非常好用！附课程的作业报告。-openCV-C++ code, using PCA algorithm for face principal component extraction and real-time facial expression recognition algorithm with kNN. Program can create their own
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用pca实现的matlab人脸表情识别程序-Pca matlab achieved with facial expression recognition program
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人脸表情检测，基于PCA算法，本代码的特点是人脸图像的检测率高-Facial expression detection algorithm based on PCA, feature of the code is that a face image detection rate
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人脸表情识别matlab程序PCA+SVM算法，SVM分类-orL人脸数据库有数据有图片-Facial expression recognition matlab program PCA+SVM algorithm, SVM classification-orL face
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Matlab表情识别，特征脸[1 ]作为面部表情分类的方法。首先，利用训练图像创建低维人脸空间（pca）。这是通过训练图像集主成分分析（PCA）及图片主成分分析（即具有较大特征值的特征向量）获得的。
结果，所有的测试图像以所选择的主成分表示，计算投影图像与所有投影列车图像的欧几里得距离，选择最小值以找出与试验图像最相似的训练图像。(The feature face [1] is used as a facial expression classification method. Firstly,
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