Chapter 1: Setting Up OpenCV
Chapter 2: Handling Files, Cameras, and GUIs
Chapter 3: Processing Images with OpenCV
Chapter 4: Depth Estimation and Segmentation
Chapter 5: Detecting and Recognizing Faces
Chapter 6: Retrieving Images and Searching Using Image Descriptors
Chapter 7: Building Custom Object Detectors
Chapter 8: Tracking Objects
Chapter 9: Camera Models and Augmented Reality
Chapter 10: Neural Networks with OpenCV - An Introduction
Appendix A: Bending Color Space with a Curves Filter

Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You’ll be able to put theory into practice by building apps with OpenCV 4 and Python 3. You’ll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you’ll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you’ll have opportunities for hands-on activities. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age. By the end of this book, you’ll have the skills you need to execute real-world computer vision projects. Summary provided by the publisher