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

Product type Paperback

Published in Dec 2018

Publisher

ISBN-13 9781789533576

Length 280 pages

Edition 3rd Edition

Languages

C++

Tools

OpenCV

Concepts

Computer Vision

Authors (2):

Roy Shilkrot

David Millán Escrivá

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Table of Contents (12) Chapters

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

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Technical requirements

The technologies and softwares used in this chapter are the following:

OpenCV v3 or v4 Android SDK compiled with the ArUco contrib module: https://github.com/Mainvooid/opencv-android-sdk-with-contrib
Android Studio v3.2+
Android device running Android OS v6.0+

Build instructions for these components, as well as the code to implement the concepts presented in this chapter, will be provided in the accompanying code repository.

To run the examples, a printed calibration board is required. The board image can be generated programmatically with the ArUco cv::aruco::CharucoBoard::draw function, and can then be printed using a home printer. The board works best if it is glued to a hard surface, such as a cardboard or plastic sheet. After printing the board, precise measurements of the board marker's size should be taken (with a ruler or caliper), to make...

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Authors (2)

Roy Shilkrot

Roy Shilkrot is an assistant professor of computer science at Stony Brook University, where he leads the Human Interaction group. Dr. Shilkrot's research is in computer vision, human-computer interfaces, and the cross-over between these two domains, funded by US federal, New York State, and industry grants. Dr. Shilkrot graduated from the Massachusetts Institute of Technology (MIT) with a PhD, and has authored more than 25 peer-reviewed papers published at premier computer science conferences, such as CHI and SIGGRAPH, as well as in leading academic journals such as ACM Transaction on Graphics (TOG) and ACM Transactions on Computer-Human Interaction (ToCHI).

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Millán Escrivá

David Millán Escrivá was 8 years old when he wrote his first program on an 8086 PC in Basic, which enabled the 2D plotting of basic equations. In 2005, he finished his studies in IT with honors, through the Universitat Politécnica de Valencia, in human-computer interaction supported by computer vision with OpenCV (v0.96). He has worked with Blender, an open source, 3D software project, and on its first commercial movie, Plumiferos, as a computer graphics software developer. David has more than 10 years' experience in IT, with experience in computer vision, computer graphics, pattern recognition, and machine learning, working on different projects, and at different start-ups, and companies. He currently works as a researcher in computer vision.

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