Description: 这是基于mean-shift运动目标跟踪的matlab仿真的程序,含有三个M文件-This is based on the mean-shift moving target tracking matlab simulation program, containing three M documents Platform: |
Size: 3072 |
Author:还非子 |
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Description: 该原代码包提供图像去噪,图像修复,求psnr值等功能。主要使用全变分方法等方法实现图像处理。-The source code package to provide image denoising, image restoration, and features such as PSNR values. The main use of methods such as variational methods realize image processing. Platform: |
Size: 389120 |
Author:Christine |
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Description: 一篇论文,讨论了基于SIFT特征的遥感影像自动配准的方法-A paper to discuss the SIFT-based features of the remote sensing image automatic registration method Platform: |
Size: 1080320 |
Author:潇布衣 |
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Description: 在Matlab中实现基于旋转尺度不变特征提取特征点的方法。-Matlab implementation of the rotation based on scale-invariant feature extraction method of feature points. Platform: |
Size: 2634752 |
Author:quanshuiwusheng |
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Description: Speeded Up Robust Features 在SIFT特正点匹配算法上进行改进,代码已完成Matlab->VC的程序打包-Speeded Up Robust Features in the SIFT matching algorithm special on-time improvement, the code has been completed Matlab-> VC packing process Platform: |
Size: 1154048 |
Author:萧峙清 |
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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: |
Size: 257024 |
Author:文松抑扬 |
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Description: 自动的角点检测算法。运用SIFT特征,对图像中的特征点进行提取!试过,好用!-Automatic corner detection algorithm. The use of SIFT features, right in the image feature point extraction! Tried, easy to use! Platform: |
Size: 4203520 |
Author:Sean |
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Description: 实现视频描述的方法,提取视频特征值,从2d-sift扩展到3d-sift-The video describes the method of extraction of video features of value, from the 2d-sift extended to 3d-sift Platform: |
Size: 1232896 |
Author:王旭晨 |
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Description: SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处理两幅图像之间发生的平移、旋转情况下的匹配问题-SIFT features matching algorithm is the hot matching algorithm of feature points at home and abroad . its matching ability is strong.It can match the feature points of two images which are rotated or traslation. Platform: |
Size: 4485120 |
Author:田晓娜 |
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Description: 这是一个著名的MATLAB/C实现的sift算法库。
并且被分解成几个可以重用的M和MEX文件。
这个实现产生一些关键点和描述子,和David Lowe s的实现差不多。-This is a MATLAB/C implementation of the SIFT detector and descriptor. It is customizable and features a decomposition of the algorithm in several reusable M and MEX files. This implementation produces interest points and descriptors which are very similar to David Lowe s implementation. Platform: |
Size: 2503680 |
Author:白水 |
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Description: 这是一个用MATLAB代码实现的一个关于图像的特征描述子的提取 以及相应特征点进行匹配的代码 可用于图像识别 或者立体匹配。-This is a MATLAB code with a descriptor on the image feature extraction and matching feature points in the corresponding code can be used for image recognition or stereo matching.
This directory contains compiled binary programs for finding SIFT
invariant features that can run under Linux or Windows. In addition,
there is a Matlab script as well as C source code showing how to load
the features and do simple feature matching. Platform: |
Size: 396288 |
Author:peter |
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Description: SURF算法,是SIFT的升级版,速度更快,性能也不差,快速实现图像特征点的检测和匹配。-SURF algorithm, is an upgraded version of SIFT, faster, not bad performance, rapid detection of image feature points and matching. Platform: |
Size: 1362944 |
Author:张东兴 |
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Description: 根据局部尺度不变特征编写的MATLAB仿真程序,经验证可以正确运行。-Prepared according to the local invariant features scale MATLAB simulation program, and is certified to run correctly. Platform: |
Size: 2659328 |
Author:陈朋 |
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Description: sift算子,提取区域特征,进行对象的检测与跟踪。(Sift operator is used to extract region features and detect and track objects.) Platform: |
Size: 995328 |
Author:Chao SIR
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