过得去RANSAC使用的5点findHomography（OpenCV进行Android版） [英] Getting the 5 points used by RANSAC in findHomography (OpenCV for Android)

问题描述

在OpenCV的针对Android，功能org.opencv.Calib3d.findHomography（..）返回齐次变换矩阵。例如，这只会返回对应性：

In OpenCV for Android, the function org.opencv.Calib3d.findHomography(..) returns the homogeneous transformation matrix. For example, this only returns the homography:

Mat homography = Calib3d.findHomography(points1, points2, Calib3d.RANSAC, 0.5);

有没有一种方法，以返回RANSAC实际上从Android OpenCV的API使用点？

Is there a way to return the points that RANSAC actually uses from the Android OpenCV API?

推荐答案

更新

我不知道它是否是一个新增加的OpenCV还是我刚刚错过了它，但<一个href=\"http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html?highlight=findhomography#Mat%20findHomography%28InputArray%20srcPoints,%20InputArray%20dstPoints,%20int%20method,%20double%20ransacReprojThreshold,%20OutputArray%20mask%29\"相对=nofollow> findHomography（）函数实际上可以给你围层（OpenCV的2.4.2）。最后一个参数，屏蔽，默认情况下是空的，将填充在由RANSAC foound内围层的那些指标（或255）。

I am not sure whether it's a new addition to OpenCV or I've just missed it, but the findHomography() function actually can give you the inliers (OpenCV 2.4.2). The last parameter, mask, which is empty by default, will be filled with ones (or 255) at the indexes of the inliers foound by RANSAC.

Mat findHomography(InputArray srcPoints, InputArray dstPoints, 
     int method=0, double ransacReprojThreshold=3, OutputArray mask=noArray() )
//                                                               ^
//                                                               |

旧的答案

使用RANSAC估计单对应性（在技术文档称为内围层）的点不能被直接提取。他们内部计算的，但随后的名单被删除。

The points used by RANSAC to estimate the homography (called inliers in technical docs) cannot be extracted directly. They are computed internally, but then the list is deleted.

提取它们的方法是修改find​​Homography功能（以及相应的RANSAC功能）。但是，这是丑陋的。

A way to extract them is to modify the findHomography function (and the corresponding RANSAC functions). But this is ugly.

另外，清洁的方法是什么测试点对输入比赛日单应：

Another, cleaner way is to test what point pairs in the input match th homography:

使用 projectPoints（points1，单应，points1_dest）（我希望这是函数名）申请单应于points1。
使用 CV ::距离（points1_dest，points2）来看看哪些是足够接近他们的points2对。距离应小于或等于 MIN_DISTANCE ^ 2 。在你的情况， 0.5×0.5 = 0.25 。

use the projectPoints(points1, homography, points1_dest) (i hope this is the function name) to apply homography to points1. use cv::distance(points1_dest, points2) to see which of them are close enough to their pair in points2. The distance should be smaller or equal to min_distance^2. In your case, 0.5*0.5 = 0.25.

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