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Learning OpenCV 4 Computer Vision with Python 3

You're reading from   Learning OpenCV 4 Computer Vision with Python 3 Get to grips with tools, techniques, and algorithms for computer vision and machine learning

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789531619
Length 372 pages
Edition 3rd Edition
Languages
Tools
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
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Joseph Howse
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Table of Contents (13) Chapters Close

Preface 1. Setting Up OpenCV 2. Handling Files, Cameras, and GUIs FREE CHAPTER 3. Processing Images with OpenCV 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. Other Book You May Enjoy Appendix A: Bending Color Space with the Curves Filter

Using ORB with FAST features and BRIEF descriptors

If SIFT is young, and SURF younger, ORB is in its infancy. ORB was first published in 2011 as a fast alternative to SIFT and SURF.

The algorithm was published in the paper ORB: an efficient alternative to SIFT or SURF, available in PDF format at http://www.willowgarage.com/sites/default/files/orb_final.pdf.

ORB mixes the techniques used in the FAST keypoint detector and the BRIEF keypoint descriptor, so it is worth taking a quick look at FAST and BRIEF first. Then, we will talk about brute-force matching – an algorithm used for feature matching – and look at an example of feature matching.

FAST

The Features from Accelerated Segment Test (FAST) algorithm works...

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