When points in the world lie on a plane and we have some calibration location information about certain points, then we can use a technique called homography to find the locations of other points from an image.

Why do we need homography?

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 computation of camera motion—rotation and translation—between two images.

What is homography in Python?

Homography is a transformation that maps the points in one point to the corresponding point in another image. The homography is a 3×3 matrix : If 2 points are not in the same plane then we have to use 2 homographs.