Description: 基于特征的影像匹配——SIFT Method!!!
相当经典,只不过是MatLab源码，希望有哪位高手能转换成VC++源码!-feature-based image matching -- physiology Method! ! ! Quite classic, MatLab is the only source, which experts hope will be converted into VC source! Platform: |
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Author:山海涛 |
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Description: 用于数据预处理的多小波分解与重构程序.其中多小波是采用CL4平衡多小波,所以分解前的预处理是采用等值预滤波器.如果要用别的非平衡多小波,只需替换为相应的预滤波器即可.-for data pretreatment multiwavelet decomposition and reconstruction process. Multiwavelet which is the Panasonic balance multiwavelets Therefore, the pretreatment before decomposition is the equivalent pre-filter. If you want other non-equilibrium multiwavelets only replacement for the corresponding pre-filter may be. Platform: |
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Author:王颖 |
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Description: 基于特征的影像匹配——SIFT Method!!!
相当经典,只不过是MatLab源码，希望有哪位高手能转换成VC++源码!-feature-based image matching-- physiology Method! ! ! Quite classic, MatLab is the only source, which experts hope will be converted into VC source! Platform: |
Size: 376832 |
Author:山海涛 |
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Description: sift算子中高斯金字塔和DOG的生成，只是该算子的最初步骤-sift operator：the generation of Gaussian pyramid and DOG。it is only the first steps Platform: |
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Author:lili |
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Description: 采用c++调用matlab写的一个sift算法，其中调用matlab只是使用其中几个函数。可以很准确的检测出sift特征点。-Using c++ to call a matlab write sift algorithm, which used to call only a few matlab function. Can accurately detect the feature points sift. Platform: |
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Author:woxiest |
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Description: 作为一种匹配能力较强的局部描述算子，SIFT算法的实现相当复杂，但从软件开发的角度来说，只要会使用其中几个比较重要的函数就行了。这里要感谢David Lowe这个大牛，不但提供了一种强悍的特征匹配算法，还给出了C++的实现代码，后来有人用C#实现了这个算法，需要的朋友可到网上自行下载。
-As a strong ability to match the partial description of operator, SIFT algorithm to achieve very complex, but software development point of view, so long as the use of a few of the more important function on the list. Here would like to thank David Lowe this big cow, not only provides a powerful feature matching algorithm, but also gives the realization of C++ code, then someone C# implements this algorithm needs a friend can be purchased online to download on their own. Platform: |
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Author:xyrx |
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Description: 不论科研还是应用上都希望可以和人类的视觉一样通过程序自 动找出两幅图像里面相同的景物，并且建立它们之间的对应，前几年才被提出的SIFT（尺度不变特征）算法提供了一种解决方法，通过这个算法可以使得满足一 定条件下两幅图像中相同景物的某些点（后面提到的关键点）可以匹配起来-Both research and application, or want to be like the human visual images by automatically identifying two inside the same scene, and the establishment of the correspondence between them, a few years ago was only made by SIFT (scale-invariant features) algorithm to provide a solution by this algorithm can make to meet certain conditions, the same two images, scene of some point (later referred to the critical point) can match the Platform: |
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Author:文松抑扬 |
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Description: 实现SIFT特征点的检测及图像拼接功能，主要在原来作者的基础上添加了显示全部特征点或者只显示重叠区域特征点，能够直接使用-Achieve SIFT feature point detection and image stitching function, mainly on the basis of the original author to add a point or show all the characteristics of overlap only feature points can be used directly Platform: |
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Author:Lukcy |
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Description: 图像的特征用到了Dense Sift，通过Bag of Words词袋模型进行描述，当然一般来说是用训练集的来构建词典，因为我们还没有测试集呢。虽然测试集是你拿来测试的，但是实际应用中谁知道测试的图片是啥，所以构建BoW词典我这里也只用训练集。
其实BoW的思想很简单，虽然很多人也问过我，但是只要理解了如何构建词典以及如何将图像映射到词典维上去就行了，面试中也经常问到我这个问题，不知道你们都怎么用生动形象的语言来描述这个问题？
用BoW描述完图像之后，指的是将训练集以及测试集的图像都用BoW模型描述了，就可以用SVM训练分类模型进行分类了。
在这里除了用SVM的RBF核，还自己定义了一种核： histogram intersection kernel，直方图正交核。因为很多论文说这个核好，并且实验结果很显然。能从理论上证明一下么？通过自定义核也可以了解怎么使用自定义核来用SVM进行分类。-Image features used in a Dense Sift, by the Bag of Words bag model to describe the word, of course, the training set is generally used to build the dictionary, because we do not test set. Although the test set is used as the test you, but who knows the practical application of the test image is valid, so I am here to build BoW dictionary only the training set.
In fact, BoW idea is very simple, although many people have asked me, but as long as you understand how to build a dictionary and how to image map to the dictionary D up on the line, and interviews are often asked me this question, do not know you all how to use vivid language to describe this problem?
After complete description of the image with BoW, refers to the training set and test set of images are described with the BoW model, the training of SVM classification model can be classified.
Apart from having to use the RBF kernel SVM, but also their own definition of a nuclear: histogram intersection kernel, histogram Platform: |
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Author:lipiji |
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Description: %this code is the Matlab implimentation of David G. Lowe,
%"Distinctive image features from scale-invariant keypoints,"
%International Journal of Computer Vision, 60, 2 (2004), pp. 91-110.
%this code should be used only for academic research.
%any other useage of this code should not be allowed without Author agreement.
% if you have any problem or improvement idea about this code, please
% contact with Xing Di, Stevens Institution of Technology. xdi2@stevens.edu Platform: |
Size: 4096 |
Author:arzehgar
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