Description: PCA算法，用于人脸识别的特征提取步骤，是目前最通用的传统的人脸识别算法。通过构建特征子空间进行降维-PCA algorithm for face recognition feature extraction step is currently the most common in traditional face recognition algorithms. By constructing feature subset space dimensionality reduction Platform: |
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Author:Jessie |
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Description: 利用Sub-pattern PCA在Yale人脸库上进行人脸识别的matlab源代码，子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-pattern PCA use in the Yale face database for face recognition on the matlab source code, sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the establishment of sub-image set, in each sub-image Set the use of PCA to extract the features, the establishment of sub-space. Treatment to identify images, by the same block, the respective sub-image to the corresponding sub-space projection, feature extraction. Finally, according to the principle of nearest neighbor classification. Platform: |
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Author:章格 |
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Description: PCA主成分分析用于人脸识别，提取特征值特征向量。有ORL人脸库。-PCA principal component analysis for face recognition, extraction Eigenvalue eigenvector. Have ORL face database. Platform: |
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Author:qjc |
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Description: MATLAB环境下编的人脸检测和识别算法，人脸识别部分采用的pca算法，另外包括一个人机界面，直接运行facedec程序即可运行-MATLAB environment, compiled by face detection and recognition algorithms, face recognition pca algorithm is used in some of the other, including a man-machine interface, programs can be run directly run the facedec Platform: |
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Author:Brad Bibson |
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Description: 摘要：主成分分析（PCA）的人脸识别算法，以减少的特征向量是涉及到对抽象的特点，改进了主成分分析（一）iUumination算法的变化影响酶原sed.The方法是基于上减低与正常化其相应的标准差的特征向量元素相关联的大特征值的特征向量的影响力的想法。耶鲁大学和耶鲁大学面临的数据库面对数据库B是用来验证-Abstract：In principal component analysis(PCA)algorithms for face recognition，to reduce the influence of the
eigenvectors which relate to the changes of the iUumination on abstract features，a modified PCA ( A)
algorithm is propo sed．The method is based on the idea of reducing the influence of the eigenvectors associated
with the large eigenvalues by normalizing the feature vector element by its corresponding standard deviation．
Th e Yale face database and Yale face database B are used to verify the method．The simulation results show
that，f0r front face and even under the condition of limited variation in the facial po ses the proposed method
results in better perform ance than the conventional PCA and linear discriminant analysis(LDA)approaches．and
the computational cost remains the same as that ofthe PCA，and much less than that ofthe LDA． Platform: |
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Author:费富里 |
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Description: 利用2DPCA和2DLDA在ORL人脸数据库上做的人脸识别实验，注解详细，适合初学者使用，对理解PCA与LDA有很大的作用。-2DPCA and 2DLDA use in ORL face database for face recognition experiments do, comment in detail, suitable for beginners, on the understanding of PCA and LDA are very useful. Platform: |
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Author:xiaocai |
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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: |
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Author:mahmoud |
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Description: 模块pca, 在人脸识别中进行特征提取，速度效率比PCA要高，基于ORL人脸库上进行试验。-In face recognition module pca feature extraction by speed, efficiency, than pca based on ORL face database on the test.
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Author:白万荣 |
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Description: Gabor小波变换与PCA的人脸识别代码，采用波束成形技术的BER计算，现代信号处理中谱估计在matlab中的使用。- Gabor wavelet transform and PCA face recognition code, By applying the beam forming technology of BER Modern signal processing used in the spectral estimation in matlab. Platform: |
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Author:戴海娟 |
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Description: 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。-Facial recognition technology as a biological feature recognition technology is an important part of, in recent years has become a hot research topic in the field of computer vision and pattern recognition.This experiment is based on K- L transform principal component analysis (PCA) in the application of face recognition, based on ORL face validation of rapid PCA algorithm was realized by Matlab simulation, and reconstructed the sample image., on the basis of the experiment on ORL face , choose top 5 pictures each, a total of 40 people 200 sample image, through rapid PCA algorithm the sample feature vector of 10304 d down to 20 d, and implements the face reconstruction based on principal component, PCA algorithm is verified in the high-dimensional data processing and feature extraction is effective to dimension reduction. Platform: |
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Author:季科 |
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Description: By matlab code, Using weighted model nodes in the network strength and weight are power law distribution, Gabor wavelet transform and PCA face recognition code. Platform: |
Size: 59392 |
Author:quipangang
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Description: 运用PCA算法，可以通过摄像头实时获取人脸，进行人脸识别。(By using PCA algorithm, we can get face in real time by camera and face recognition.) Platform: |
Size: 40960 |
Author:123456hh |
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Description: MATLAB课堂考勤（GUI）
该课题为基于MATLAB pca的人脸考勤系统。可以从一副图像中找出多人人脸，分割，计算人数，然后提前制作好这些人的人脸库，进行逐一识别是谁，是不是库内人脸，如是，具体是谁，如果不是，那提示库外人脸。具有友好的人机交互界面，还可以二次开发成摄像的，但是摄像头误差可能会有点。识别流程为：读取图像，人脸定位，人数统计，人脸分割，人脸识别，库内外判别。(The subject is face attendance system based on MATLAB PCA. We can find multiple faces from an image, segment and calculate the number of people, and then make a face database of these people in advance to identify who they are one by one, whether they are the faces in the database, if so, who they are, and if not, prompt the faces outside the database. It has a friendly human-computer interface and can be developed into a camera again, but the camera error may be a little bit. The recognition process includes: image reading, face location, number of people statistics, face segmentation, face recognition, identification inside and outside the database.) Platform: |
Size: 18601984 |
Author:for Matlab |
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