Hello everybody. I am trying to use findHomography but I have some issues. Indeed, I have two set of points containing numerous outliers. When I try to apply findHomography to these dataset, the H matrix becomes totally crazy. As I have many outilers I use CV_RANSAC option, but maybe it is not enough ? If I take a look to this code: http://docs.opencv.org/2.4/doc/tutorials/features2d/feature_homography/feature_homography.html I can see that only "probable good matches" are used in the function findHomography. But I thought that was the goal of the RANSAC algorithm ? Am I wrong ? I cannot use the previsous code because I find the point in my own way (each points are in fact stars in astronomical images)
So what I have to do to my datasets before to inject them in findHomography ?
Here two sets of points giving wrong transformation matrix: https://drive.google.com/open?id=0B2ywocsrHgKdT0NvN1owS1Bmbkk https://drive.google.com/open?id=0B2ywocsrHgKdWHJJME1QeGhCTXM
Cheers,