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Description: pca人脸识别This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames
Platform: |
Size: 2636 |
Author: 蔡加欣 |
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Description: PCA人脸识别
This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames
Platform: |
Size: 3317 |
Author: 蔡加欣 |
Hits:
Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames
Platform: |
Size: 2353 |
Author: 蔡加欣 |
Hits:
Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames
Platform: |
Size: 967 |
Author: 蔡加欣 |
Hits:
Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames
Platform: |
Size: 1480 |
Author: 蔡加欣 |
Hits:
Description: PCA 人脸识别, PCA 人脸识别,PCA 人脸识别-PCA face recognition, face recognition PCA, the PCA face recognition, face recognition PCA
Platform: |
Size: 33792 |
Author: |
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Description:
Platform: |
Size: 2048 |
Author: 蔡加欣 |
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Description: PCA人脸识别
This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames-PCA Face Recognition This package implements basic Principal Component Analysis in Matlab andtests is with grayscale portion of the FERET database. Images are notpreprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: |
Size: 3072 |
Author: 蔡加欣 |
Hits:
Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames
Platform: |
Size: 2048 |
Author: 蔡加欣 |
Hits:
Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames-PCA Face Recognition This package implements basic Principal Component Analysis in Matlab andtests is with grayscale portion of the FERET database. Images are notpreprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: |
Size: 1024 |
Author: 蔡加欣 |
Hits:
Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames-PCA Face Recognition This package implements basic Principal Component Analysis in Matlab andtests is with grayscale portion of the FERET database. Images are notpreprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: |
Size: 1024 |
Author: 蔡加欣 |
Hits:
Description: 对人脸识别的贝叶斯方法ML中相似度计算公式进行了简化，对数据集的训练和人脸图像的预处理进
行了修改，提出了一种改进的贝叶斯人脸识另1】算法SML。在FERET人脸图像库的子集和南大人脸图像实验库上对
识别算法进行了测试和比较。实验表明，SML算法提高了ML算法的效率，克服了ML算法计算效率不高的缺陷，而
且SML的识别效率明显高于PCA方法。-Bayesian face recognition method on the ML in the similarity formula has been simplified, the data set of training and pre-processing face images were modified, an improved understanding of Bayesian Face Ling 1】 algorithm SML. In the FERET face image database a subset of the Southern adults face image recognition algorithm on the experimental database was tested and compared. Experiments show that, SML algorithm improves the efficiency of ML algorithm, ML algorithm overcomes the shortcomings of high efficiency, and the recognition rate significantly higher than SML PCA method.
Platform: |
Size: 262144 |
Author: dmay |
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Description: Principal Component Analysis on the FERET Dataset, 人臉辨識系統使用 PCA 應用在 FERET 人臉資料庫, 提供完整的 matlab 源碼.
Platform: |
Size: 34816 |
Author: 王扶助 |
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Description: 这是一个Matlab编写的基于PCA的人脸识别分类算法，对FERET数据库进行了分类。-This is a Matlab prepared by the PCA based face recognition algorithm, the FERET database are classified.
Platform: |
Size: 67584 |
Author: 李岩 |
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Description: 针对feret人脸数据库，对传统pca算法的实现。-For feret Face database, to achieve the traditional pca algorithm.
Platform: |
Size: 30720 |
Author: le |
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Description:
This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames.
pca.m and createDistMat.m can be used on any database following the
same principles described in the header of the files. feret.m is specific
for the FERET database but can easily be transformed to be generic if needed.
In addition to the three .m files, standard FERET gallery and probe set lists
are given, along with a list of randomly chosen 500 images that can be used
for testing:
Training set: trainList.mat
Gallery: feretGallery.mat
Probe sets: fb.mat fc.mat dup1.mat dup2.mat-
This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the filenames.
pca.m and createDistMat.m can be used on any database following the
same principles described in the header of the files. feret.m is specific
for the FERET database but can easily be transformed to be generic if needed.
In addition to the three .m files, standard FERET gallery and probe set lists
are given, along with a list of randomly chosen 500 images that can be used
for testing:
Training set: trainList.mat
Gallery: feretGallery.mat
Probe sets: fb.mat fc.mat dup1.mat dup2.mat
Platform: |
Size: 34816 |
Author: harish bsv |
Hits: