The goal of this book is to get you hands-on with a wide range of intermediate to advanced projects using the latest version of the OpenCV 4 framework and the Python 3.8 language instead of only covering the core concepts of computer vision in theoretical lessons.
This updated second edition has increased the depth of the concepts we tackle with OpenCV. It will guide you through working on independent hands-on projects that focus on essential computer vision concepts such as image processing, 3D scene reconstruction, object detection, and object tracking. It will also cover, with real-life examples, statistical learning and deep neural networks.
You will begin by understanding concepts such as image filters and feature matching, as well as using custom sensors such as the Kinect depth sensor. You will also learn how to reconstruct and visualize a scene in 3D, how to align images, and how to combine multiple images into a single one. As you advance through the book, you will learn how to recognize traffic signs and emotions on faces and detect and track objects in video streams using neural networks, even if they disappear for short periods of time.
By the end of this OpenCV and Python book, you will have hands-on experience and be proficient at developing your own advanced computer vision applications according to specific business needs. Throughout the book, you will explore multiple machine learning and computer vision models such as Support Vector Machines (SVMs) and convolutional neural networks.
