I know that one can compute the homography matrix by using at least four correpondence points.
I was wondering if and how can I obtain a homography matrix if I already know the rotation and translation between two cameras, including the camera intrinsics?
I found something that looked like this
H= KRK^-1
but this assumes a pure rotation. What would be the case for a pure translation? And what if I want to warp an image with the homography matrix that is not from points purely on a plane?
I'm somewhat confused right now and would really really appreciate any explanations! Thank you in advance!
In the field of computer vision, any two images of the same planar surface in space are related by a homography (assuming a pinhole camera model). This has many practical applications, such as image rectification, image registration, or camera motion—rotation and translation—between two images.
We have seen that a homography can be used to map one image to the other in the case of pure camera rotation or a planar scene. If such a homography exists between the images, four points are sufficient to specify it precisely.
Homography lets us relate two cameras viewing the same planar surface; Both the cameras and the surface that they view (generate images of) are located in the world-view coordinates. In other words, two 2D images are related by a homography H, if both view the same plane from a different angle.
If there is a nonzero translation, and the image contains more than a plane (or you are not looking at very far away things) then the images are not related by a homography. You can convince yourself that this is the case by noticing that some points visible in one image may be occluded in the other one.
If the image shows a plane among other things, and you estimate a homography using only point correspondences on that plane, than the homography will correctly transform all points on that plane, but will map incorrectly all other points.
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