Book Image

Mastering OpenCV 3 - Second Edition

By : Jason Saragih
Book Image

Mastering OpenCV 3 - Second Edition

By: Jason Saragih

Overview of this book

As we become more capable of handling data in every kind, we are becoming more reliant on visual input and what we can do with those self-driving cars, face recognition, and even augmented reality applications and games. This is all powered by Computer Vision. This book will put you straight to work in creating powerful and unique computer vision applications. Each chapter is structured around a central project and deep dives into an important aspect of OpenCV such as facial recognition, image target tracking, making augmented reality applications, the 3D visualization framework, and machine learning. You’ll learn how to make AI that can remember and use neural networks to help your applications learn. By the end of the book, you will have created various working prototypes with the projects in the book and will be well versed with the new features of OpenCV3.
Table of Contents (14 chapters)
Title Page
Mastering OpenCV 3 Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Introduction to face recognition and face detection


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 a computer to learn to recognize a known face. These generally involve four main steps:

  1. Face detection: This is the process of locating a face region in an image (a 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 more clear and similar to other faces (a small grayscale face in the top-center of the following screenshot).
  3. Collecting and learning faces: This is the process of saving many preprocessed faces (for each person that should be recognized), and then learning how to recognize them.
  4. Face recognition: This is the process that checks which of the collected people are most similar...