Description: 表情识别程序，连上摄像头之后通过视频进行表情识别-Expression recognition process, connected to the camera through the video after the expression recognition Platform: |
Size: 107520 |
Author:reginadeng |
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Description: 針對單一人臉做出五官的檢測定位,並在人臉上畫出五官的方框作為表示.-For a single human face detection features make positioning, and his face painted in the box as an express facial features. Platform: |
Size: 3072 |
Author:李毅駿 |
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Description: 对由光源颜色变化引起的图像色彩偏差,进行了校正,并在YCbCr颜色空间建立了Cb-Cr色度查找表和亮度信息联合的肤色模型,应用预处理技术,去除部分非人脸区域,减少人脸检测的搜索空间,并采用模板匹配方法在人脸候选区域检测人脸.实验表明,该方法能够有效的从复杂环境的彩色图像中检测出左右旋转不超过45°的人脸,且不受人脸表情、尺度和数目的影响,且错误率较低.-Color by the light source caused by the change of image color deviation, a correction, and YCbCr color space established a Cb-Cr chrominance and luminance information look-up table of the color model of the joint application of pre-treatment technology, to remove some non-human face region, Face detection to reduce the search space, using a template matching method in the face candidate region detection of human faces. experiments show that the method can be effective in complex environments from color images detected no more than about 45 ° rotation of the human face, and from Facial Expression, scale and number of impact, and lower error rate. Platform: |
Size: 191488 |
Author:lll |
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Description: 擅 蔓：以人脸的表情识别为实验背景， 分析了在对人脸表情的识别过程中，单个独立分薰对识别率的影响，由此进一步总结了在表情识
别中如何更有效地选取独立子空间，以实现在不影响识别率的前提下，减少用于构成独立子空问所需的独立分量的个数。 独立成分分析；表情识别；独立子空间 -Good man: Face to face identification for the experimental background, the analysis of facial expressions in the identification process, a single smoked separate the impact of the recognition rate, thus further summarized in the expression recognition of how to more effectively select the independent sub-space in order to achieve the recognition rate does not affect the premise, for constituting a separate sub-reducing space required for the number of independent component. Independent component analysis expression recognition independent subspace Platform: |
Size: 272384 |
Author:金振东 |
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Description: 在广泛研究前人工作的基础上，本文对运动人物的检测、跟踪与识别进行了综述。为
使分类清楚明了，本文将人物运动分析分为两大类：人体运动分析，人脸分析。人体运动分
析包括人的较大幅度的肢体运动，如手势识别、步态分析、整个人体的运动分析；人脸分析
包括人脸检测与识别、表情分析。在详细介绍了国内外研究现状后，提出了存在的问题及研
究前景。-Extensively studied in previous work on the basis of the figures in this article on the movement detection, tracking and recognition are reviewed. To enable a clear understanding of classification, motion analysis of figures in this article will be divided into two categories: human motion analysis, analysis of human faces. Analysis of human motion including the relatively large body movements, such as gesture recognition, gait analysis, motion analysis of the human body Facial analysis includes face detection and recognition, facial expression analysis. In the study described in detail the status quo at home and abroad, the proposed study of the problems and prospects. Platform: |
Size: 357376 |
Author:martin |
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Description: 3种Gabor滤波器的表达方法，采用MATLAB编写，可用于人脸的识别-Gabor filters of three kinds of expression, the use of MATLAB to prepare, can be used for face recognition Platform: |
Size: 2048 |
Author:xzg |
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Description: 结合人脸肤色和发色进行的人脸检测，可以忽略人脸的姿态表情，不用进行人脸特征的定位-Combination of face color and hair color for face detection, facial gesture can ignore the expression, do not carry out the positioning of facial features Platform: |
Size: 1024 |
Author:gu |
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Description: 基于高波滤波的特征提取技术，从而实现人脸识别和表情识别的目的-Based on high-wave filter feature extraction techniques, in order to achieve the purpose of face recognition and expression recognition Platform: |
Size: 19272704 |
Author:hefangfang |
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Description: 为了更有效地提取图像的局部特征，提出了一种基于2维偏最小二乘法(two—dimensional partial least
square，2DPLS)的图像局部特征提取方法，并将其应用于面部表情识别中。该方法首先利用局部二元模式(1ocal
binary pattern，LBP)算子提取一幅图像中所有子块的纹理特征，并将其组合成局部纹理特征矩阵。由于样本图像
被转化为局部纹理特征矩阵，因此可将传统PLS方法推广为2DPLS方法，用来提取其中的判别信息。2DPLS方法
通过对类成员关系矩阵的构造进行相应的修改，使其适应样本的矩阵形式，并能体现出人脸局部信息重要性的差
异。同时，对于类成员关系协方差矩阵的奇异性问题，也推导出了其广义逆的解析解。基于JAFFE人脸表情库的
实验结果表明，该方法不但可以有效地提取图像局部特征，并能取得良好的表情识别效果。-To better the image of the local feature extraction, a partial least squares method based on 2D (two-dimensional partial least
square, 2DPLS) image local feature extraction method, and applied to facial expression recognition. In this method, use of local binary pattern (1ocal
binary pattern, LBP) operator extracts an image texture features of all sub-blocks, and their combination into the local texture feature matrix. As the sample image
Be translated into the local texture feature matrix, so the traditional PLS method can be generalized to 2DPLS method used to extract the identification information. 2DPLS method
Through the class membership matrix in the corresponding modifications to adapt the sample matrix, and can reflect the importance of face poor local information
Different. Meanwhile, members of the class covariance matrix of the singular relations issues, also derived the generalized inverse of the analytical solution. Based on the JAFFE facial expression database
Platform: |
Size: 315392 |
Author:MJ |
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Description: One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Transform with Perceptron Neural Network.. and the other based on Discrete Cosine Transform with Perceptron Neural Network ...
2- In face expression recognition .. we defined the condition of the person (nature,happiness,disgust or anger)
this source code is based on Principle component analysis(PCA) ..
* we need to now about digital image processing
,neural network and PCA-One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Transform with Perceptron Neural Network.. and the other based on Discrete Cosine Transform with Perceptron Neural Network ...
2- In face expression recognition .. we defined the condition of the person (nature,happiness,disgust or anger)
this source code is based on Principle component analysis(PCA) ..
* we need to now about digital image processing
,neural network and PCA... Platform: |
Size: 11905024 |
Author:mahmoud |
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Description: 基于matlab的人脸表情是别的Gabor小波特征提取-Matlab-based face expression is other Gabor little potter character extraction Platform: |
Size: 1024 |
Author:吴会霞 |
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Description: 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, a low-dimensional face space (pca) is created using training images. This is obtained by training principal component analysis (PCA) of image set and principal component analysis of image (i.e. eigenvectors with larger eigenvalues).
As a result, all the test images are represented by the selected principal components, the Euclidean distance between the projected image and all the projected train images is calculated, and the minimum value is selected to find the training image most similar to the test image.) Platform: |
Size: 4684800 |
Author:bbqQq |
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Search - face expression matlab