June 2019
Intermediate to advanced
348 pages
8h 28m
English
Content preview from Qt 5 and OpenCV 4 Computer Vision Projects
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Detecting objects using OpenCV
There are many approaches to object detection in OpenCV. These approaches can be categorized as follows:
- Color-based algorithms such as meanshift and Continuously Adaptive Meanshift (CAMshift)
- Template matching
- Feature extracting and matching
- Artificial Neural Networks (ANNs)
- Cascade classifier
- Pretrained deep learning models
The first three are the traditional approaches to object detection, while the last three are approaches of machine learning.
The color-based algorithms, such as meanshift and CAMshift, use histograms and back-projection images to locate an object in an image with incredible speed. The template matching approach uses the object of interest as a template and tries to find the object by ...
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.