March 2019
Intermediate to advanced
538 pages
13h 38m
English
book
Building Computer Vision Projects with OpenCV 4 and C++
by David Millan Escriva, Prateek Joshi, Vinicius G. Mendonca, Roy Shilkrot
Content preview from Building Computer Vision Projects with OpenCV 4 and C++
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Lucas-Kanade method
The Lucas-Kanade method is used for sparse optical flow tracking. By sparse, we mean that the number of feature points is relatively low. You can refer to their original paper here: http://cseweb.ucsd.edu/classes/sp02/cse252/lucaskanade81.pdf. We start the process by extracting the feature points. For each feature point, we create 3 x 3 patches with the feature point at the center. The assumption here is that all the points within each patch will have a similar motion. We can adjust the size of this window depending on the problem at hand.
For each feature point in the current frame, we take the surrounding 3 x 3 patch as our reference point. For this patch, we look in its neighborhood in the previous frame to get the ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.