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Homography Explained with Code
Prev Tutorial: AKAZE and ORB planar tracking Introduction This tutorial will demonstrate the basic concepts of the homography with some codes. For detailed explanations about the theory, please refer to a computer vision course or a computer vision book, e.g.: - Multiple View Geometry in Computer Vision, Richard Hartley and Andrew Zisserman, [117] (some sample chapters are available here, CVPR Tutorials are available here) - An Invitation to 3-D Vision: From Images to Geometric Models, Yi Ma, Stefano Soatto, Jana Kosecka, and S.
This is a quick solution (see also ) as this does not ensure that the resulting rotation matrix will be orthogonal and the scale is estimated roughly by normalize the first column to 1. The result of the decomposition of the homography matrix can only be recovered up to a scale factor that corresponds in fact to the distance d as the normal is unit length. To illustrate, we used Blender, a free and open-source 3D computer graphics software, to generate two camera views with only a rotation transformation between each other.
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