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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

Implementing SfM in OpenCV

OpenCV has an abundance of tools to implement a full-fledged SfM pipeline from first principles. However, such a task is very demanding and beyond the scope of this chapter. The former edition of this book presented just a small taste of what building such a system will entail, but luckily now we have at our disposal a tried and tested technique integrated right into OpenCV's API. Although the sfm module allows us to get away with simply providing a non-parametric function with a list of images to crunch and receive a fully reconstructed scene with a sparse point cloud and camera poses, we will not take that route. Instead, we will see in this section some useful methods that will allow us to have much more control over the reconstruction and exemplify some of the topics we discussed in the last section, as well as be more robust to noise.

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