OpenCV Essentials

Acquire, process, and analyze visual content to build full-fledged imaging applications using OpenCV

• Set up OpenCV, its Python bindings, and optional Kinect drivers on Windows, Mac or Ubuntu
• Create an application that tracks and manipulates faces
• Identify face regions using normal color images and depth images

This book is intended for C++ developers who want to learn how to implement the main techniques of OpenCV and get started with it quickly. Working experience with computer vision / image processing is expected.

OpenCV, arguably the most widely used computer vision library, includes hundreds of ready-to-use imaging and vision functions used in both academia and industry. It mainly focuses on real-time image processing. As cameras get cheaper and imaging features grow in demand, the range of applications using OpenCV increases significantly, both for desktop and mobile platforms.

The book provides an example-based tour of OpenCV's main modules and algorithms, including the latest available in version 3.0. Starting with the setup and description of the library, this book teaches you how to add graphical user interface capabilities to OpenCV programs. Further, you will learn about the essential techniques such as image processing, image segmentation, object detection, and motion, which will help you process and analyze images better. You will also learn how to extract 2D features from images and how to take advantage of machine learning. By the end of this book, you will completely understand how to put those computer vision techniques into practice.