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This thesis presents a comprehensive overview of the problem of facial recognition. A survey of available facial detection algorithms as well as implementation and tests of di铿
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Facial Feature Extraction Using Geometric Feature and ICA
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Improved Active Shape Model for Facial Feature
Extraction in Color Images
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运用于人脸识别中的特征提取方法：通过稀疏化特征向量（即使一些不重要的特征值为0），来减少运算量-Used in face recognition feature extraction methods: by sparse feature vector (even if some important features of value 0), to reduce the computation
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In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. With the weights of the trained neural networks there are created kernel window
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combined pattern search optimization of feature extraction and classification parameters in facial recognition
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利用主元分析和奇异值分解进行人脸特征提取的方法(并详细阐述其在PQRSQT中的实现过程(包括读取图像文件U计算均值脸U求特征值和特征向量(计算人脸特征参数-实现过程均给出了MATLAB代码-Using principal component analysis and singular value decomposition facial feature extraction method (and detail its in the PQRSQT in the implementation pr
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Development of the Facial Feature Extraction and Emotion
Recognition Method based on ASM and Bayesian Network
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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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为了实现复杂环境下的人脸特征有效表达，提出一种改进的梯度方向直方图（ＨＯＧ）人脸识别方法．首先以人脸图像网格作为采样窗口并在其上提取 ＨＯＧ特征；然后将所有网格 ＨＯＧ特征向量进行组合，实现整个人脸特
征表达；最后采用最近邻分类器进行识别．另外，比较了该方法与Ｇａｂｏｒ小波和局部二值模式（ＬＢＰ）２种著名的人脸
局部特征表示方法的优劣．实验结果表明，在调优的 ＨＯＧ参数下，在具有光照和时间环境等复杂变化的ＦＥＲＥＴ人
脸库中，较少维数的 ＨＯＧ特征比ＬＢＰ特征有更好的表现，而且 ＨＯ
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sir i want the source code and document of facial feature extraction, facial classification and facial expression recognition.
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This project describes the problem of facial expression recognition in the field of computer vision. Firstly, the psychological background of the problem is presented. Then, the idea of facial expression recognition system (FERS) is outlined and the
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This project describes the problem of facial expression recognition in the field of computer vision. Firstly, the psychological background of the problem is presented. Then, the idea of facial expression recognition system (FERS) is outlined and the
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人脸识别技术作为生物体特征识别技术的重要组成部分，在近些年来已经发展成为计算机视觉和模式识别领域的研究热点。本实验是基于K-L变换的主成分分析法（PCA）在人脸识别中的应用，在ORL人脸库的基础上通过Matlab实现了快速PCA算法的验证仿真，并对样本图像进行了重构。本实验在ORL人脸库的基础上，选用每人前5张图片，共计40人200幅样本图像，通过快速PCA算法将10304维的样本特征向量降至20维，并实现了基于主分量的人脸重建，验证了PCA算法在高维数据降维处理与特征提取方面的有效性。-Fac
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FACE DETECTION 用于人脸检测 特征点提取(FACE DETECTION. Facial feature extraction and representation.)
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