homography

I'm using findHomography on a list of points and sending the result to warpPerspective . The problem is that sometimes the result is complete garbage and the resulting image is represented by weird gray rectangles. How can I detect when findHomography sends me bad results? There are several sanity tests you can perform on the output. On top of my head: Compute the determinant of the homography, and see if it's too close to zero for comfort. Even better, compute its SVD, and verify that the ratio of the first-to-last singular value is sane (not too high). Either result will tell you whether the

I want to calculate my camera's position in world coordinates. This should be fairly easy, but I don't get the results I expect. I believe I've read everything on this topic, but my code isn't working. Here's what I do: I have a camera looking at an area. 1) I drew a map of the area. 2) I calculated the homography by matching 4 image points to 4 points on my map using cv2.getPerspectiveTransform 3) The H homography transforms every world coordinate to camera coordinate; this is working properly 4) To calculate the camera matrix I followed this : translation = np.zeros((3,1)) translation[:,0] =

This might have been answered but I desperately need an answer for this. I want to find the largest square or rectangle in an image using OpenCV in Android. All of the solutions that I found are C++ and I tried converting it but it doesn't work and I do not know where I'm wrong. private Mat findLargestRectangle(Mat original_image) { Mat imgSource = original_image; Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY); Imgproc.Canny(imgSource, imgSource, 100, 100); //I don't know what to do in here return imgSource; } What I am trying to accomplish in here is to create a new image that

This question was already asked , but I still don't get it. I obtain a homography matrix by calling cv::findHomography from a set of points. I need to check whether it's relevant or not. The proposed method is to calculate maximum reprojection error for inliers and compare it with a threshold. But after such filtration I keep getting insane transformations with object bounding box transforming to almost a straight line or some strange non-convex quadrangle, with self-intersections etc. What constraints can be used to check if the homography matrix itself is adequate? DanielHsH Your question is

I've a calibrated camera where I exactly know the intrinsic and extrinsic data. Also the height of the camera is known. Now I want to virtually rotate the camera for getting a Bird's eye view, such that I can build the Homography matrix with the three rotation angles and the translation. I know that 2 points can be transformed from one image to another via Homography as x=K*(R-t*n/d)K^-1 * x' there are a few things I'd like to know now: if I want to bring back the image coordinate in ccs, I have to multiply it with K^-1, right? As Image coordinate I use (x',y',1) ? Then I need to built a