Seeing the algorithm in action
The result of the matching procedure in a live stream from my laptop's webcam looks like this:
As you can see, most of the keypoints in the pattern image were matched correctly with their counterparts in the query image on the right. The printout of the pattern can now be slowly moved around, tilted, and turned. As long as all the corner points stay in the current frame, the homography matrix is updated accordingly and the outline of the pattern image is drawn correctly.
This works even if the printout is upside down, as shown here:
In all cases, the warped image brings the pattern image to an upright, centered position ...
Get OpenCV: Computer Vision Projects with Python now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
