搜索资源列表
draw-characteristic-and-match
- 用sift方法检测图像的特征点，并且求出特征向量从而匹配图像。-Sift method is used to inspect the image feature points, and to find the feature vector which match the image.
siftDemoV4
- sift描述子,用来提取特征点以及匹配 计算机视觉的重要基础-sift descr iptors important foundation for extracting feature points and matching of computer vision
asift_Algorithm
- 实现图像的自动配准，是SIFT算法的改进算法，同时在ASIFT匹配阶段，对算法进行了修改，采用KD树结构进行搜索。-Automatic registration of images is SIFT algorithm improved algorithm, while ASIFT matching stage, the algorithm was modified using the KD tree search.
SIFT_stitching
- 输入两幅图像，查找SIFT特征点，显示两张图的匹配点，并对图形进行拼接，效果不错。-Enter the two images, find SIFT feature point matching point display two graphs, graphics stitching, good results.
siftDemoV4
- 图像匹配 sift算法实现 match直接调用函数即可 -sift image matching algorithm
OPENCV_SIFT
- 用openCV进行sift特征提取和匹配-sift feature detection and matching using openCV
OpenSURFCSharp
- 比传统的图像匹配方法更好，相对于SIFT\SURF算法运行速率提高-Improve OpenSURF c# version
Patch
- 1利用SIFT关键点进行图像匹配 2在视频中，在一帧中检测关键点，之后利用canonical patch传递关键点，经过一定阈值的帧后，再次计算关键点，利用相邻帧之间关键点的差别很小，只更新关键点的位置，提高帧率。 3阈值自动确定-1 uses SIFT image matching key points 2 in the video, detecting critical points in one frame, after which it canonical patch tra
3D-Reconstruction.
- 择了一种速度、特征点数量和精度都比较好的组合方案：FAST角点检测算法+sift特征描述子+FLANN(Fast Library for Approximate Nearest Neighbors) 匹配算法。-Choose a speed and precision of the number of feature points are relatively good combination scheme: FAST corner detection algorithm+sift featur
SIFTpractice
- SIFT算法的实现，图形匹配源代码，可直接使用-SIFT algorithm implementations, pattern matching source code can be used directly
face-detect
- 在安卓NDK下实现了图像的sift检测，可以圈出特征点，并且能够匹配二幅图像，需要opencv库支持。-In the android to realize the image under the NDK sift detection, can circle the feature points, and the ability to match two images, need opencv library support.
FEATUREDECTECTION
- 几种图像匹配算法的比较，SIFT,SURF,HARRIS-SIFT等算法，利用GUI清晰可以看出区别-Comparison of several image matching algorithm, SIFT, SURF, HARRIS-SIFT algorithms, the GUI can clearly see the difference
RobustMatch
- 基于opencv，讲述关于SIFT、SURF、ORB、FREAK、FAST、BRIEF等方法用于图像的特征提取以及匹配之间的不同-Based on opencv, about SIFT, SURF, ORB, FREAK, FAST, and BRIEF, used for image feature extraction and matching between different
plot
- 使用sift+RANSAC完成两幅图像的特征提取和匹配，并将较小图像区域在另一幅中用方框圈出来。运行plot.m。-This code uses sift and RANSAC to extract features of two images and then finds and marks the smaller image in the other image.run plot.m
Image-mosaic
- 图像拼接，可以将两张分开的图片进行对接。原理是利用sift特征进行匹配-Mosaic, which can dock two separate image. Principle is to use sift feature matching
TestSift_match
- SIFT 算法进行匹配，是许多图像应用的基础-SIFT matching algorithm is the basis for many imaging applications
code
- 本程序主要描述了几种彩色图像的特征提取的方法，包含颜色、纹理、的特征提取，还有图像的分割、sift特征点的提取与匹配。-In this experiment an extracting features image based on content is designed.color and texture feature extraction methods are described.There are some segmentation methods and sift key poi
SIFTMATCH
- 利用SIFT算法，用opencv的2.4.9的库进行目标的匹配和定位-using the SIFT algorithm,match the object with opencv lib
IDAc
- 基于边缘的模板匹配,很重要，匹配很好的,能计算结果，有帮助的-SIFT descr iptor matching，it s very important, and very useful
hesaff-master
- 影像仿射变换特征提取，结合 sift 等局部特征可以处理较大视角变化下的图像匹配。-This is an implementation of Hessian-Affine detector.