Description: 模式识别中人连识别眼镜定位，用的是matlab支持向量机开发的-human pattern recognition to identify even glasses positioning, using the Matlab SVM Development Platform: |
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Author:网小强 |
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Description: 二维线性鉴别分析(2DLDA)算法能有效解决线性鉴别分析(LDA)算法的“小样本”效应，支持向量机
(SVM)具有结构风险最小化的特点，将两者结合起来用于人脸识别。首先，利用小波变换获取人脸图像的低频分量，忽
略高频分量：然后，用2DLDA算法提取人脸图像低频分量的线性鉴别特征，用“一对多”的SVM 多类分类算法完成人脸
识别。基于ORL人脸数据库和Yale人脸数据库的实验结果验证了2DLDA+SVM算法应用于人脸识别的有效性。-”Small sample size”problem of LDA algorithm can be overcome by two—dimensional LDA f 2DLDA)，and
Support Vector Machine(SVM)has the characteristic of structural risk minimization．In this paper，two methods were
combined and used for face recognition．Firstly，the original images were decomposed into high—frequency and low—frequency
components by Wavelet Transform(WT)．The high—frequency components were ignored，while the low—frequency components
can be obtained．Then．the liner discriminant features were extracted by 2DLDA，and”one VS rest”。strategy of SVMs for
muhiclass classification was chosen to perform face recognition． Experimental results based on ORL f Olivetti Research
Laboratory1 face database and Yale face database show the validity of 2DLDA+SVM algorithm for face recogn ition． Platform: |
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Author:费富里 |
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Description: 支持向量机及其在人脸识别中的应用研究
上海交通大学博士论文，在知网上面付费下载得到的。本文从应用的角度出发，较为全面地对一些相关问题进行探讨，并使用Visual C++实现了一个基于支持向量机的人脸识别软件—idTeller。 论文的主要工作和创新点包括： ·提出了两种基于VC边界的支持向量机参数选择算法—固定C算法和VC-CV算法。VC边界是两类支持向量机参数选择的一个理想准则，但它的一些固有缺点使其应用变得困难。本文通过将VC边界转化为VC指标，最终把问题归结为对最小包围体的求解，从理论上和计算上为VC边界的使用铺平了道路。在此基础之上，本文提出了两种基于VC边界的参数选择算法—固定C算法和VC-CV算法。在数个基准数据集上的实验表明，相比交叉验证算法，VC-CV算法不仅能获得性能更好的分类器，而且具有较低的计算复杂度。 ·使用序贯最小优化算法解决了最小包围体求解问题。最小包围体求解是计算VC指标的一个关键步骤，本文使用序贯最小优化算法对其求解，并对算法初始化、参数选择及更新等若干实现问题进行了深入地研究。在多个基准数据集上的实验表明，序贯最小优化算法能够快速而准确地解决最小包围体求解问题。-
Support vector machine and its application to face recognition
Shanghai Jiaotong University doctoral thesis, in HowNet above pay to get the download. From the application point of view, to more fully explore some related issues, and using Visual C-idTeller a support vector machine-based face recognition software. The main work and innovation of the paper include: two kinds of parameters of support vector machine based on the VC boundary selection algorithm- fixed-C algorithm and the VC-CV algorithm. VC boundaries are two types of support vector machine parameters to select the ideal criteria, but some of its inherent shortcomings make it difficult. This article by VC boundary for the VC index, and ultimately the problem is reduced to the solution of the minimum bounding volume, and paved the way for the use of the VC boundary from the theory and calculations. On this basis, we propose two parameter selection algorithm based on the VC boundary- fixed-C algorithm and the VC-CV algorit Platform: |
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Author:Jessicaying |
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Description: 用2DPCA提取人脸特征，然后用支持向量机分类识别。效果不错。-With 2 DPCA face feature extraction, and then by support vector machines (SVM) classification and recognition. The result is right.
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Author:huanli |
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Description: opencv最新书籍《Master OpenCV with Practical Computer Vision Projects》。基于opencv2.4.3编写。采用了实例工程方式讲解。-opencv book:
Chapters:
Ch1) Cartoonifier and Skin Changer for Android, by Shervin Emami.
Ch2) Marker-based Augmented Reality on iPhone or iPad, by Khvedchenia Ievgen.
Ch3) Marker-less Augmented Reality, by Khvedchenia Ievgen.
Ch4) Exploring Structure from Motion using OpenCV, by Roy Shilkrot.
Ch5) Number Plate Recognition using SVM and Neural Networks, by David Escrivá.
Ch6) Non-rigid Face Tracking, by Jason Saragih.
Ch7) 3D Head Pose Estimation using AAM and POSIT, by Daniel Lélis Baggio.
Ch8) Face Recognition using Eigenfaces or Fisherfaces, by Shervin Emami.
Ch9) Developing Fluid Wall using the Microsoft Kinect, by Naureen Mahmood.
Platform: |
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Author:王邦平 |
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Description: 本程序中，利用了LBP特征对人脸特征进行提取，并且利用SVM对提取的人脸特征进行训练和识别，其中，所用的图像处理库OpenCV2.4.9版本；通过对人脸库中的标准标本进行测试，算法识别率高达95%以上；(LBP features extract facial features, and use SVM to extract and recognize the facial features. The OpenCV2.4.9 version of the image processing library is used. The recognition rate of the algorithm is over 95% by testing the standard samples in the face database.) Platform: |
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Author:丽丽6663142 |
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