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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
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David Millán Escrivá
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Toc

Table of Contents (12) Chapters Close

Preface 1. Cartoonifier and Skin Color Analysis on the RaspberryPi 2. Explore Structure from Motion with the SfM Module FREE CHAPTER 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

Technical requirements

These technologies and installations are required to build and run the code in this chapter:

  • OpenCV 4 (compiled with the sfm contrib module)
  • Eigen v3.3+ (required by the sfm module)
  • Ceres solver v2+ (required by the sfm module)
  • CMake 3.12+
  • Boost v1.66+
  • OpenMVS
  • CGAL v4.12+ (required by OpenMVS)

The build instructions for the components listed, as well as the code to implement the concepts in this chapter, will be provided in the accompanying code repository. Using OpenMVS is optional, and we may stop after getting the sparse reconstruction. However, the full MVS reconstruction is much more impressive and useful; for instance, for 3D printing replicas.

Any set of photos with sufficient overlap may be sufficient for 3D reconstruction. For example, we may use a set of photos I took of the Crazy Horse memorial head in South Dakota that is bundled with this...

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Mastering OpenCV 4 - Third Edition
Published in: Dec 2018
Publisher:
ISBN-13: 9781789533576
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