December 2012
Intermediate to advanced
340 pages
8h 3m
English
Content preview from Mastering OpenCV with Practical Computer Vision ProjectsBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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POSIT
After we have found the 2D position of our landmark points, we can derive the 3D pose of our model using the POSIT. The pose P of a 3D object is defined as the 3 x 3 rotation matrix R and the 3D translation vector T, hence P is equal to [ R | T ].
Note
Most of this section is based on the OpenCV POSIT tutorial by Javier Barandiaran.
As the name implies, POSIT uses the Pose from Orthography and Scaling (POS) algorithm in several iterations, so it is an acronym for POS with Iterations. The hypothesis for its working is that we can detect and match in the image four or more non-coplanar feature points of the object and that we know their relative geometry on the object.
The main idea of the algorithm is that we can find a good approximation to ...
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