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Mastering OpenCV 4

You're reading from   Mastering OpenCV 4 A comprehensive guide to building computer vision and image processing applications with C++

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Product type Paperback
Published in Dec 2018
Publisher
ISBN-13 9781789533576
Length 280 pages
Edition 3rd Edition
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Authors (2):
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Roy Shilkrot Roy Shilkrot
Author Profile Icon Roy Shilkrot
Roy Shilkrot
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Table of Contents (12) Chapters Close

Preface 1. Cartoonifier and Skin Color Analysis on the RaspberryPi FREE CHAPTER 2. Explore Structure from Motion with the SfM Module 3. Face Landmark and Pose with the Face Module 4. Number Plate Recognition with Deep Convolutional Networks 5. Face Detection and Recognition with the DNN Module 6. Introduction to Web Computer Vision with OpenCV.js 7. Android Camera Calibration and AR Using the ArUco Module 8. iOS Panoramas with the Stitching Module 9. Finding the Best OpenCV Algorithm for the Job 10. Avoiding Common Pitfalls in OpenCV 11. Other Books You May Enjoy

Avoiding Common Pitfalls in OpenCV

OpenCV has been around for more than 15 years now. It contains many implementations that are outdated or unoptimized and are relics of the past. An advanced OpenCV engineer should know how to avoid basic mistakes in navigating the OpenCV APIs, and see their project to algorithmic success.

In this chapter, we will review the historic development of OpenCV, and the gradual increase in the framework and algorithmic offering, alongside the development of computer vision at large. We will use this knowledge to see how to figure out whether a newer alternative exists within OpenCV for our algorithm of choice. Lastly, we will discuss how to identify and avoid common problems or sub-optimal choices while creating computer vision systems with OpenCV.

The following topics will be covered in this chapter:

  • A historic review of OpenCV and the latest wave...
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