homography

问题 I have already done the comparison of 2 images of same scene which are taken by one camera with different view angles(say left and right) using SURF in emgucv (C#). And it gave me a 3x3 homography matrix for 2D transformation. But now I want to make those 2 images in 3D environment (using DirectX). To do that I need to calculate relative location and orientation of 2nd image(right) to the 1st image(left) in 3D form. How can I calculate Rotation and Translate matrices for 2nd image? I need

问题 I am using the function findHomography of OpenCV with the RANSAC method in order to find the homography that relates two images linked with a set of keypoints. Main issue is that I haven’t been able to find anywhere yet what are the values of the mask matrix that the function outputs. Only information that I know is that 0 values are outliers, and non zero values are inliers. But what does it mean the inliers value? Anyone knows? Thanks in advance! Piece of code where I call findHomography :

问题 This question is on the OpenCV functions findHomography , getPerspectiveTransform & getAffineTransform What is the difference between findHomography and getPerspectiveTransform ?. My understanding from the documentation is that getPerspectiveTransform computes the transform using 4 correspondences (which is the minimum required to compute a homography/perspective transform) where as findHomography computes the transform even if you provide more than 4 correspondencies (presumably using

问题 I have a panorama image, and a smaller image of buildings seen within that panorama image. What I want to do is recognise if the buildings in that smaller image are in that panorama image, and how the 2 images line up. For this first example, I'm using a cropped version of my panorama image, so the pixels are identical. import cv2 import matplotlib.pyplot as plt import matplotlib.image as mpimg import numpy as np import math # Load images cwImage = cv2.imread('cw1.jpg',0) panImage = cv2

问题 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? 回答1: 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

问题 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

问题 I found the Homography matrix following the Feature Matching + Homography tutorial using M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,5.0) and now I need to warp the second image (rotated one) to match the keypoints of the first one, so I tried to do with warpPerspective directly on img2 since we have the Homography matrix already. (They did not use warpPersective in the tutorial) dst = cv2.warpPerspective(img2, M) and it complains that I'm missing the third argument TypeError:

问题 I've 2 pictures of the same scene from an uncalibrated camera. The pics are from a slightly different angle and scale(zoom) and I'd like to superpose them, rejecting any kind of shake. In other words, I should transform them so the shake becomes imperceptible, do a Motion Compensation. I've already tried using a simple SURF (feature) detector along with Homography but sometimes the result isn't satisfactory. So I am thinking about trying Image Rectification to compensate the motion. - Would

问题 I wish to stitch two or more images using OpenCV and C++. The images have regions of overlap but they are not being detected. I tried using homography detector. Can someone please suggest as to what other methods I should use. Also, I wish to use the ORB algorithm, and not SIFT or SURF. The images can be found at- https://drive.google.com/open?id=133Nbo46bgwt7Q4IT2RDuPVR67TX9xG6F 回答1: This a very common problem. Because images like this, they actually do not have much in common. The overlap

问题 I'm building an application in Java that uses OpenCV. I haven't used the library before, and the Java implementation is a bit lacking in documentation. I need to undo a perspective warped image to make it squared up. I need to transform a trapezoid to a rectangle. Basically I need to stretch the shorter of the two parallel sides to match the length of the longer parallel side. I know I need to compute homographies and use a WarpPerspective function, but I have no idea how to structure this