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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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Toc

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

Introduction to face detection and face recognition

Face recognition is the process of putting a label to a known face. Just like humans learn to recognize their family, friends, and celebrities just by seeing their face, there are many techniques for recognize a face in computer vision.

These generally involve four main steps, defined as follows:

  1. Face detection: This is the process of locating a face region in an image (the large rectangle near the center of the following screenshot). This step does not care who the person is, just that it is a human face.
  2. Face preprocessing: This is the process of adjusting the face image to look clearer and similar to other faces (a small grayscale face in the top center of the following screenshot).
  3. Collecting and learning faces: This is a process of saving many preprocessed faces (for each person that should be recognized), and then learning...
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