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Learn OpenCV 4 by Building Projects

Learn OpenCV 4 by Building Projects

By : Millán Escrivá, Vinícius G. Mendonça, Joshi
2.5 (2)
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Learn OpenCV 4 by Building Projects

Learn OpenCV 4 by Building Projects

2.5 (2)
By: Millán Escrivá, Vinícius G. Mendonça, Joshi

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. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.
Table of Contents (14 chapters)
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Detecting Face Parts and Overlaying Masks

In Chapter 6, Learning 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...

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