Book Image

Mastering OpenCV 4 - Third Edition

By : Roy Shilkrot, David Millán Escrivá
Book Image

Mastering OpenCV 4 - Third Edition

By: Roy Shilkrot, David Millán Escrivá

Overview of this book

Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.
Table of Contents (12 chapters)

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...