sift
所属分类：3D图形编程
开发工具：Visual C++
文件大小：8577KB
下载次数：19
上传日期：2012-03-05 22:49:22
上 传 者：
mvpmiao
说明： SIFT特征（Scale-invariant feature transform，尺度不变特征转换)是一种电脑视觉的算法用来侦测与描述影像中的局部性特征，它在空间尺度中寻找极值点，并提取出其位置、尺度、旋转不变量，此算法由 David Lowe 在1999年所发表，2004年完善总结。其应用范围包含物体辨识、机器人地图感知与导航、影像缝合、3D模型建立、手势辨识、影像追踪和动作比对。
(Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.[1]
Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, and match moving.)
文件列表:
sift\.svn\entries (6495, 2009-06-01)
sift\.svn\format (2, 2009-06-01)
sift\.svn\prop-base\Arab hotel_1.bmp.svn-base (53, 2009-06-01)
sift\.svn\prop-base\Arab hotel_2.bmp.svn-base (53, 2009-06-01)
sift\.svn\prop-base\beaver.png.svn-base (53, 2009-06-01)
sift\.svn\prop-base\beaver_xform.png.svn-base (53, 2009-06-01)
sift\.svn\prop-base\ImgMosaic.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\ImgMosaic1.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\pan00.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\pan01.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\pan02.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\pan03.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\Photo_1.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\Photo_2.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\s1.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\s2.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\stacked_refine.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\stacked_refine0.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\stacked_refine_1.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\sub1.JPG.svn-base (53, 2009-06-01)
sift\.svn\prop-base\sub2.JPG.svn-base (53, 2009-06-01)
sift\.svn\prop-base\Thumbs.db.svn-base (53, 2009-06-01)
sift\.svn\prop-base\tilt0-50.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\tilt_0_50.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\video01 008-0000000.jpg.svn-base (53, 2009-06-01)
sift\.svn\prop-base\video01 008-0000043.jpg.svn-base (53, 2009-06-01)
sift\.svn\text-base\Arab hotel_1.bmp.svn-base (842104, 2009-06-01)
sift\.svn\text-base\Arab hotel_2.bmp.svn-base (2199608, 2009-06-01)
sift\.svn\text-base\beaver.png.svn-base (48824, 2009-06-01)
sift\.svn\text-base\beaver.sift.svn-base (43721, 2009-06-01)
sift\.svn\text-base\beaver_xform.png.svn-base (39513, 2009-06-01)
sift\.svn\text-base\H.txt.svn-base (5161, 2009-06-01)
sift\.svn\text-base\H_1.txt.svn-base (16954, 2009-06-01)
sift\.svn\text-base\imgfeatures.c.svn-base (16331, 2009-06-01)
sift\.svn\text-base\imgfeatures.h.svn-base (3730, 2009-06-01)
sift\.svn\text-base\ImgMosaic.jpg.svn-base (67397, 2009-06-01)
sift\.svn\text-base\ImgMosaic1.jpg.svn-base (310710, 2009-06-01)
sift\.svn\text-base\kdtree.c.svn-base (14909, 2009-06-01)
sift\.svn\text-base\kdtree.h.svn-base (3166, 2009-06-01)
sift\.svn\text-base\LoadImg.txt.svn-base (128, 2009-06-01)
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Contents:1. Intro2. Requirements3. Running
4. Output
1. Intro
This is a project to find a homography of two images which are to be registrated .
They are matched with a feature-based registration method which implements SIFT features .
For more information, refer to:
Lowe, D. Distinctive image features from scale-invariant keypoints.International Journal of Computer Vision, 60, 2 (2004),pp.91--110.
Or see Lowe's website:
http://www.cs.ubc.ca/~lowe/keypoints/
2. Requirements
All code in this package requires the OpenCV library (known working
version is 1.0.0):http://sourceforge.net/projects/opencvlibrary/
Of coures , you must figure opencv into visual c++ after the installation.
3.Running
The codes are written in c language .
Main function is in match.c
The compile mode is c compiler . It is figured in visual studio 2003 in such way:
project--properties--c/c++ --Advanced--Compiles as --(choose)Compile as c code
In mathc.c ,you can change your input files and output files .
4.Output
The sift keypoints of two image .
The tranformed image wiht homography .
The homography matrix is outputed in the H.txt
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