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 9. Learning Object Tracking

In the previous chapter, we learned about video surveillance, background modeling, and morphological image processing. We discussed how we can use different morphological operators to apply cool visual effects to input images. In this chapter, we are going to learn how to track an object in a live video. We will discuss the different characteristics of an object that can be used to track it. We will also learn about different methods and techniques for object tracking. Object tracking is used extensively in robotics, self-driving cars, vehicle tracking, player tracking in sports, and video compression.

By the end of this chapter, you will know the following:

  • How to track objects of a specific color
  • How to build an interactive object tracker
  • What a corner detector is
  • How to detect good features to track
  • How to build an optical flow-based feature tracker