Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By : David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Chapter 7. Detecting Face Parts and Overlaying Masks

In Chapter 6Learning Object Classification, we learned about object classification and how machine learning can be used to achieve it. In this chapter, we are going to learn how to detect and track different face parts. We will start the discussion by understanding the face detection pipeline and how it's built. We will then use this framework to detect face parts, such as the eyes, ears, mouth, and nose. Finally, we will learn how to overlay funny masks on these face parts in a live video.

By the end of this chapter, we should be familiar with the following topics:

  • Understanding Haar cascades
  • Integral images and why we need them
  • Building a generic face detection pipeline
  • Detecting and tracking faces, eyes, ears, noses, and mouths in a live video stream from the webcam
  • Automatically overlaying a face mask, sunglasses, and a funny nose on a person's face in a video