Learn to capture videos, manipulate images and track objects with Python using the OpenCV Library
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
Computer Vision can reach consumers in various contexts via webcams, camera phones and gaming sensors like Kinect. OpenCV's Python bindings can help developers meet these consumer demands for applications that capture images, change their appearance and extract information from them, in a high-level language and in a standardized data format that is interoperable with scientific libraries such as NumPy and SciPy.
"OpenCV Computer Vision with Python" is a practical, hands-on guide that covers the fundamental tasks of computer vision—capturing, filtering and analyzing images—with step-by-step instructions for writing both an application and reusable library classes.
"OpenCV Computer Vision with Python" shows you how to use the Python bindings for OpenCV. By following clear and concise examples you will develop a computer vision application that tracks faces in live video and applies special effects to them. If you have always wanted to learn which version of these bindings to use, how to integrate with cross-platform Kinect drivers and and how to efficiently process image data with NumPy and SciPy then this book is for you.