September 2019
Intermediate to advanced
420 pages
10h 29m
English
book
Machine Learning for OpenCV 4 - Second Edition
by Aditya Sharma, Michael Beyeler (USD), Vishwesh Ravi Shrimali, Michael Beyeler
Content preview from Machine Learning for OpenCV 4 - Second Edition
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Taking a glimpse at the histogram of oriented gradients (HOG)
The HOG might just provide the help we're looking for in order to get this project done. The HOG is a feature descriptor for images, much like the ones we discussed in Chapter 4, Representing Data and Engineering Features. It has been successfully applied to many different tasks in computer vision but seems to work especially well for classifying people.
The essential idea behind HOG features is that the local shapes and appearance of objects within an image can be described by the distribution of edge directions. The image is divided into small connected regions, within which a histogram of gradient directions (or edge directions) is compiled. Then, the descriptor is assembled ...
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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.