Description: Haar-Like Feature臉部辨識程式及源代碼,是研究快速臉部辨識的好例程-Haar-Like Feature facial recognition programs and source code, is to study the fast face recognition in a good routine Platform: |
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Author:賴永成 |
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Description: 摘 要： 提出了一种基于改进 Ha u s d o r f f距离的人脸相似度匹配的方法， 该方法首先将人脸划分为脸型、 双眼、 鼻、 嘴等几个特征点
集， 分别计算各部分的改进 Ha u s d o r f f 距离， 然后进行加权计算相似度。利用该方法， 在 A S M( 主动形状模型) 定位人脸的基础上进
行了人脸检索。 实验表明， 利用人脸相似度计算方法对人脸特征库进行搜索， 达到 了较好的效果。同时结合 A S M 自动人脸检测， 本
方法可以全自动完成人脸匹配， 应用于人脸识别及数字娱乐等领域。-Abstract: This paper presents a distance based on an improved Ha usdorff face similarity matching method, which will first face is divided into face, eyes, nose, mouth, and several other feature point sets, were calculated to improve the various parts of Ha usdorff distance, and then weighted similarity. Using this method, in the ASM (active shape model) positioned on the basis of human face human face retrieval. Experiments show that the use of face similarity calculation method for facial feature database to search, to achieve good results. ASM automatically combined with face detection, this method can be completed fully automatic human face matching, used in face recognition and digital entertainment and other fields. Platform: |
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Author:alsocc |
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Description: 人脸识别－仅对静态图片The output of this code is mainly required for feature detection or facial expression recognition purpose.
give the input(name of the image) at the 1st line of the facedetection.m file & run the file.
The face_database folder contain some images on which the code gave favorable output.
-The code will work with the images which don t have much brightness variation on the face.the face must be properly enlighten.
The output of this code is mainly required for feature detection or facial expression recognition purpose.
give the input(name of the image) at the 1st line of the facedetection.m file & run the file.
The face_database folder contain some images on which the code gave favorable output.
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Author:djh |
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Description: This a simple program that uses distance tool in matlab to determine geometry feature of the face, which then can be classification or clustering , or face recognition-This is a simple program that uses distance tool in matlab to determine geometry feature of the face, which then can be classification or clustering , or face recognition Platform: |
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Author:Imanuel |
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Description: 本文设计基于DCT的人脸识别系统，首先结合当今人脸识别的背景和发展状况讨论了人脸识别的研究内容及在各方面的应用；然后研究了人脸识别进行预处理，讨论了人脸识别预处理的其他方法，分析各种方法的利弊，最后采用DCT（离散余弦变换）实现人脸图像预处理中的降维处理；接下来对人脸图像的特征提取进行了研究，简单叙述了几何特征提取和代数特征提取，同时深入研究了基于DCT和PCA变换的人脸图像特征提取，从而实现是否对人脸识别系统识别率有所提高的研究；对于分类器的选择，本文对两种分类器进行了探讨，即最近邻分类器和BP神经网络分类器，同时采用BP神经网络分类器作为本次基于DCT的人脸识别系统设计的分类器，并对BP神经网络进行分类的算法进行设计，BP神经网络具有学习功能，只要采用本系统对训练图片进行训练，就可以记下图像的相关信息，对于测试图片，就可以很准确的识别出该图片是属于哪个的。最后，本文对整个人脸识别系统设计实验进行了实验分析，实验结果表明本文采用的方法切实有效。- This is the design of the DCT-based face recognition systems. First of all, the background light of the current face recognition and face recognition to discuss the development of research in all aspects of content and applications And then studied the pretreatment of face recognition to discuss the pre-treatment of other face recognition methods,and analysis of the pros and cons of various methods, finally, the use of DCT (discrete cosine transform) image pre-processing to achieve in the face of the reduced-order processing Next on the face image feature extraction have been studied, A brief description of the feature extraction and algebraic geometry feature extraction, while in-depth study based on the DCT and the PCA Transform face image feature extraction in order to achieve face recognition system to identify whether the rate of increase in the research For the choice of classifier, this paper carried out on two of classifier, that is, nearest neighbor classifier and BP neura Platform: |
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Author:刘文珍 |
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Description: 2dpca源代码，用于人脸识别，直接作用于矩阵提取特征。-2dpca the source code for face recognition, feature extraction directly on the matrix. Platform: |
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Author:gu |
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Description: lda线性特征提取，用于人脸识别，首先进行小波特征提取后用lda提取特征。-lda linear feature extraction for face recognition, first of all, after feature extraction using wavelet feature extraction using lda. Platform: |
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Author:gu |
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Description: 首先进行小波变换，在此基础上进行pca特征提取，在进行lda特征提取，用于人脸识别-First, wavelet transform, in this based on pca feature extraction, feature extraction during lda for face recognition Platform: |
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Author:gu |
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Description: 通过KL变换实现特征提取从而达到表情识别以及人脸识别的目的-By KL Transform feature extraction so as to achieve the purpose of face recognition and face recognition Platform: |
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Author:hefangfang |
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Description: 特征提取是模式识别研究领域的一个热点.本文提出了一种基于独立成分分析和线性鉴别分析的特征提取方法.谊方法中引入了零空间的概念,指出了前人算法中的不足之,并且给出了一个完整的独立成分分析和线性鉴别分析的组合算法.在ORL和Yale人脸数据库上的实验表明了该方法的有效性.-Feature extraction is a hot field of pattern recognition research. In this paper, which is based on independent component analysis and linear discriminant analysis feature extraction method. Yi method introduced the concept of zero-space, pointing out that the algorithm predecessors shortcomings, and gives a complete independent component analysis and linear discriminant analysis of the combined algorithm. In the ORL and Yale face database, the experiment shows the effectiveness of this method. Platform: |
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Author:费富里 |
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Description: 线性判别分析(LDA)是一种较为普遍的用于特征提取的线性分类方法。但是将LDA直接用于人脸识别
会遇到维数问题和“小样本”问题。人们经过研究，通过多种途径解决了这两个问题并实现了基于I,DA的人脸识
别 文章对几种基于LDA的人脸识别方法做了理论上的比较和实验数据的支持，这些方法包括Eigenfaces、Fish—
erfaceS、DLDA、VDLDA及VDFLDA。实验结果表明VDFLDA是其中最好的一种方法。-Low—dimensional feature representation with enhanced discriminatory power is of paramount importance to face
recognition(FR)system．Linear Discriminant Analysis(LDA)is one of the most popular linear classification techniques of
feature extraction。but it will meet two problems as computational challenging and “small sample size’’when applying to
face recognition directly．After studying people solve the two problems through several ways and realize the face recogni—
tion based on LDA． The short paper here makes compare on theory and experimental data analysis on several Face
Recognition system using LDA—Based Algorithm，such as Eigenfaces(using PCA)，Fisherfaces，DLDA，VDLDA and VD—
FLDA．The experimental results show that the VDFLDA method is the best of al1． Platform: |
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Author:费富里 |
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Description: 人脸识别文章 Uncorrelated Discriminant Nearest Feature Line Analysis for Face Recognition-Face article Uncorrelated Discriminant Nearest Feature Line Analysis for Face Recognition Platform: |
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Author:杜君卓 |
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Description: ：针对传统Gabor变换在提取表情特征时，冗余较大、特征维数较高的不足，结合ASM
自动特征定位技术，提出了一种基于特征点Gabor特征和ASM 形状特征相融合的面部表情
识别方法．实验表明，两种特征的融合，可有效地利用特征点的局部纹理信息和脸部器官的整
体形状信息，达到了更好的面部表情识另4效果．-: Gabor transform traditional expression feature extraction, the redundancy large feature dimension is high enough, combined with ASM automatic feature location technique, the algorithm based on feature characteristics of Gabor features and the ASM shape fusion of facial expression recognition Methods. Experimental results show that the integration of two features, feature points can effectively use the local texture information and the overall shape of the face organs of information, to achieve a better effect of facial expression understanding the other 4. Platform: |
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Author:MJ |
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Description: 提出了基于特征融合和模糊核判别分析(FKDA)的面部表情识别方法。首先，从每幅人脸图像中手工定
位34个基准点，作为面部表情图像的几何特征，同时采用Gabor小波变换方法对每幅表情图像进行变换，并提取基
准点处的Gabor小波系数值作为表情图像的Gabor特征；其次，利用典型相关分析技术对几何特征和Gabor特征进
行特征融合，作为表情识别的输人特征；然后，利用模糊核判别分析方法进一步提取表情的鉴别特征；最后，采用最
近邻分类器完成表情的分类识别。通过在JAFFE国际表情数据库和Ekman“面部表情图片”数据库上的实验，证实
了所提方法的有效性。-Proposed based on feature fusion and fuzzy kernel discriminant analysis (FKDA) facial expression recognition. First, face images of each piece of hand-set
Bit 34 basis points, as the geometric features of facial expression images, while using Gabor wavelet transform method to transform the images of each piece of expression, and extraction-based
Quasi-point of the Gabor wavelet coefficients, as Gabor features of facial expression image second, using canonical correlation analysis on the geometric features and Gabor features into
Line feature fusion, as expression recognition of input features then, using fuzzy kernel discriminant analysis method to extract and further identification features of expression Finally, the most
Neighbor classifier to complete expression of the classification. International expression by JAFFE database and Ekman "facial image" database on the experiment, confirmed
The proposed method. Platform: |
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Author:MJ |
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Description: 实现了人脸跟踪识别以及特征检测的功能，该程序支持AVI的视频图像检测-Achieved recognition and face tracking feature detection function, the program supports AVI video image detection Platform: |
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Author:yanghuajun |
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Description: This paper presents a hybrid framework of feature extraction and hidden Markov modeling (HMM) for two-dimensional pattern recognition. Importantly, we explore a new discriminative training criterion to assure model compactness and discriminability. This criterion is derived from the hypothesis test theory via maximizing the confidence of accepting the hypothesis that observations are from target HMM states rather than competing HMM states. Accordingly, we develop the maximum confidence hidden Markov modeling (MC-HMM) for face recognition. Platform: |
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Author:rupesh |
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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: This thesis relates to the design, implementation and evaluation of statis¬ tical face recognition techniques. In particular, the use of Hidden Markov Models in various forms is investigated as a recognition tool and critically evaluated. Current face recognition techniques are very dependent on issues like background noise, lighting and position of key features (ie. the eyes, lips etc.). Using an approach which specifically uses an embedded Hidden Markov Model along with spectral domain feature extraction techniques, shows that these dependencies may be lessened while high recognition rates are maintained. Platform: |
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Author:ivan |
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Search - face feature recognition