Description: 有应用matlab进行编程的源代码.m文件,以及运行需要的图象文件.-Matlab Applications for the program source code. M documents needed for the operation and image files. Platform: |
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Author:马燕 |
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Description: Malic是一个完整的Linux下的人脸识别系统源代码，它是SourceForge上的一个开源项目，使用Malib实现实时处理，CSU Face Identification Evaluation System进行人脸识别。算法包括：主成份分析(principle components analysis (PCA)),a.k.a eigenfaces算法,混合主成份分析,线性判别分析(PCA+LDA),图像差分分类器(IIDC),弹性图像匹配算法(EBGM)-Malic is a complete face recognition system under the Linux source code, it is a SourceForge open source project, using real-time Malib treatment, CSU Face Identification Evaluation System for Face Recognition. Algorithms include: Principal component analysis (principle components analysis (PCA)), aka eigenfaces algorithm, mixed-principal component analysis, linear discriminant analysis (PCA+ LDA), the image difference classifier (IIDC), a flexible image matching algorithm (EBGM) Platform: |
Size: 977920 |
Author:严锐 |
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Description: Malic是一个完整的Linux下的人脸识别系统源代码，它是SourceForge上的一个开源项目，使用Malib实现实时处理，CSU Face Identification Evaluation System进行人脸识别。算法包括：主成份分析(principle components analysis (PCA)),a.k.a eigenfaces算法,混合主成份分析,线性判别分析(PCA+LDA),图像差分分类器(IIDC),弹性图像匹配算法(EBGM)-Malic is a complete face recognition system under the Linux source code, it is a SourceForge open source project, using real-time Malib treatment, CSU Face Identification Evaluation System for Face Recognition. Algorithms include: Principal component analysis (principle components analysis (PCA)), aka eigenfaces algorithm, mixed-principal component analysis, linear discriminant analysis (PCA+ LDA), the image difference classifier (IIDC), a flexible image matching algorithm (EBGM) Platform: |
Size: 1326080 |
Author:张晓 |
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Description: 采用特征脸的人脸识别MATLAB程序,识别特定的人脸-Eigenfaces for Face Recognition using MATLAB procedures, identify a specific face Platform: |
Size: 74752 |
Author:陈炜 |
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Description: 它是SourceForge上的一个开源项目，使用Malib实现实时处理，CSU Face Identification Evaluation System进行人脸识别。算法包括：主成份分析(principle components analysis (PCA)),a.k.a eigenfaces算法,混合主成份分析,线性判别分析(PCA+LDA),图像差分分类器(IIDC),弹性图像匹配算法(EBGM)等等
Malic is realtime face recognition system that based on Malib and CSU Face Identification Evaluation System (csuFaceIdEval). Uses Malib library for realtime image processing and some of csuFaceIdEval for face recognition.-It is a SourceForge open source project, using real-time Malib processing, CSU Face Identification Evaluation System for Face Recognition. Algorithms include: Principal component analysis (principle components analysis (PCA)), aka eigenfaces algorithm, mixed-principal component analysis, linear discriminant analysis (PCA+ LDA), the image difference classifier (IIDC), a flexible image-matching algorithm (EBGM), etc. such as Malic is realtime face recognition system that based on Malib and CSU Face Identification Evaluation System (csuFaceIdEval). Uses Malib library for realtime image processing and some of csuFaceIdEval for face recognition. Platform: |
Size: 1326080 |
Author:乔超 |
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Description: Amir Hossein Omidvarnia用matlab编写的基于PCA的人脸识别系统和基于FLD的人脸识别系统,其中
的图像示例为Essex face database中 face94 的部分图像,文献可参考"Eigenfaces vs. Fisherfaces:
Recognition using class specific linear projection."已经测试过程序可正常运行没有问题。-Amir Hossein Omidvarnia prepared using matlab Face Recognition System Based on PCA and FLD-based face recognition systems, which sample the image of Essex face database for ' face94' part of images, documents may refer to " Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. " procedures have been tested there is no problem to normal operation. Platform: |
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Author:刘子木 |
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Description: 人脸识别进展
人脸识别最新的进展-2009-Face recognition is still a vividly researched area in computer science. First attempts
were made in early 1970-ies, but a real boom happened around 1988, parallel with a large
increase in computational power. The first widely accepted algorithm of that time was the
PCA or eigenfaces method, which even today is used not only as a benchmark method to
compare new methods to, but as a base for many methods derived from the original idea. Platform: |
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Author:HK |
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Description: 计算机人脸识别技术( Face Reocgnition)就利用计算机分析人脸图像,从中提取出有效的识别信息,用来辨认身份的一门技术。[ 1 ]即对已知人脸进行标准化处理后,通过某种方法和数据库中的人脸样本进行匹配,寻找库中对应人脸及该人脸相关信息。人脸自动识别系统有两个主要技术环节,一是人脸定位,即从输入图像中找到人脸存在的位置,将人脸从背景中分割出来,二是对标准化后的人脸图像进行特征提取和识别。本文中介绍的PCA (特征脸)方法就是一种常用的人脸
特征提取方法。-Computer Face Recognition Technology (Face Reocgnition) on the use of computer analysis of facial image, to extract the valid identification information used to identify the status of a technology. [1] that is known to standardize treatment of face, through a method and a database of face samples for matching, search library, the corresponding face and the face-related information. Automatic face recognition system has two main technical aspects, first, face location, that is, from the input image to find the location of the face there, the faces will be split out from the background, the second is, the standard features of face images extraction and recognition. Described in this paper PCA (Eigenfaces) method is a common facial feature extraction method. Platform: |
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Author:Highjoe |
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Description: principal component analysis (PCA ) is a well known approach for dimensionality reduction of the feature space. It has been successfully applied in face recognition. The main idea is to decompose face images into a small set of feature images called eigenfaces, which can be considered as points in a linear subspace called “face space” or “eigenspace” Platform: |
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Author:omid |
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Description: Teaching about pca - principal component analysis. you can learn how pca work and what eigenfaces is? Platform: |
Size: 219136 |
Author:numwan |
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Description: Eigenfaces are a set of eigenvectors used in the computer vision problem of human face recognition. The approach of using eigenfaces for recognition was developed by Sirovich and Kirby (1987) and used by Matthew Turk and Alex Pentland in face classification. It is considered the first successful example of facial recognition technology.[citation needed] These eigenvectors are derived from the covariance matrix of the probability distribution of the high-dimensional vector space of possible faces of human beings. Platform: |
Size: 1024 |
Author:pongpan |
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Description: This a code in matlab for face recognition using PCA-This is a code in matlab for face recognition using PCA Platform: |
Size: 2048 |
Author:Dungttn |
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Search - eigenfaces for recognition