搜索资源列表
projective-and-affine
- 基于三维空间三角网格的二维投影图像变换，包括3D仿射变换，基础矩阵求解及欧式空间的重构，对基于图像的三维重构有研究的朋友可以看下-triangular grid transform two-dimensional projection images, including 3D affine transformation, based Matrix Solution and European space reconstruction, based on the three-dimensional
sxt_bdjuzh
- 这个程序主要采用的是“最佳仿射标定矩阵”,这是部分程序-this procedure is mainly used in the "best affine calibration matrix", which is part of the process
ch6_ex6_3
- 透视变换代码 除了3*3矩阵和三个控点变为四个控点外，透视变换在其他方面与仿射变换完全类似-Perspective transformation code in addition to 3* 3 matrix and the three control points into four control points, the perspective transformation in other areas with similar affine transformation complete
Test2D
- 仿射变换与摄影变换，通过最小二乘算法计算变换矩阵。具体要有像点坐标文件，读取相应的文件即可在图上显示三位点的位置-Transformation affine transformation and photography, through the transformation matrix least-squares algorithm. Point coordinates should be as specific documents, read the corresponding docume
image-stitching
- 实验两张图片的拼接，对于图片中的匹配对，用ransac方法消除错配，并估计出仿射矩阵。然后将一张图进行仿射变换，再实现拼接-Experiment two pictures of the stitching, matching pairs for the picture, with ransac way to eliminate mismatches, and to estimate the affine matrix. Then an affine transformation diagram,
51622408Demo001
- 基于三维空间三角网格的二维投影图像变换，包括3D仿射变换，基础矩阵求解及欧式空间的重构，对基于图像的三维重构有研究的朋友可以看下 -Medical image visualization technologies build 3D models with 2D medical image series to provide useful and precise information for the doctors. It is one of the crucial technologies
CV5
- 本程序功能是由运动（估计）恢复仿射结构，具体使用的是factorization分解法。这个方法的本质就是一个矩阵分解的过程：对于给定n个点的m幅图像，我们可以写成一个2m*n的矩阵D=（q1，q2，…，qn），而这个像点矩阵可以表示成一个2m*3矩阵和一个3*n矩阵的乘积，即D=AP，其中A、P分别表示实际（仿射）摄像机位移和场景状态，也就是我们需要求得的矩阵。而如何根据D来得到A、P，正是factorization分解法的工作。-This program features the recove
sxt_bdjuzh
- 这个程序主要采用的是“最佳仿射标定矩阵”,这是部分程序-this procedure is mainly used in the " best affine calibration matrix" , which is part of the process
sxt_bdjuzh
- 这个程序主要采用的是“最佳仿射标定矩阵”,这是部分程序-this procedure is mainly used in the " best affine calibration matrix" , which is part of the process
image-mosaic
- 图像拼接，利用SIFT算法提取点特征，并进行点匹配，解算单应性矩阵，根据结算出的单应性矩阵对图像进行仿射变换，最后进行拼接，程序中的备注很详细，各位感兴趣的同志可以下载看看。-Image mosaic using SIFT feature point extraction algorithm, and point matching, homography matrix solver, based on the settlement of the homography image affine t
opencv1
- opencv仅仅实现图片倾斜，求仿射矩阵时，仅前三个点即可-Opencv to realize image tilt, only strives for the affine matrix, only the first three points
ransac1
- 使用 RANSAC 算法计算仿射变换矩阵-RANSAC algorithm using an affine transformation matrix
matlab
- 使用的版本：64位的MATLAB R2015b，代码可以直接运行仿真。 （1）提取五个特征量中的Hu矩和仿射不变矩； （2）picture用来存放训练样本和测试样本； （3）save用来保存代码运行过程中提取的特征量，matlab1存放仿射不变矩特征量， matlab2存放Hu矩特征量，Hu_BBA存放样本的Hu矩的基本信度赋值和识别类型， FS_BBA存放样本的仿射不变矩的基本信度赋值和识别类型，目标识别矩阵、信息融 果和判决结果在指令窗输出（1,2,3表示类型，
birds-eye
- 鸟瞰图变换实例，通过读取摄像机内外参数矩阵和放仿射变换的到的单应性矩阵，获得平面视图的“俯视图”。-Aerial view transform instance, affine transformation to homography by reading the internal and external camera parameters matrix and put, get a plan view of the " plan view."
automate_image
- DIC测试，适用于二维数字图像相关法，采用的ZNSSD，输入图像需为灰度图像，输出仿射矩阵(Measuring strain in samples which are too small, big, compliant, soft or hot are typical scenarios where non-contact techniques are needed. A technique which can cover all that and also can deal with comp
最小二乘法估计仿射矩阵
- 目前MATLAB里边对于多点计算仿射矩阵普遍采用RANSAC法，但是比较麻烦计算量也相对较大，通过最小二乘法来进行仿射矩阵的估计能够大大提高该效率，所以奉上自己在实验室写的仿射矩阵估计函数，来弥补matlab函数库在这方面的不足。(The MATLAB inside for calculating affine matrix commonly used RANSAC method, but more trouble calculation is relatively large, estimat