This chapter shows how to use data from a depth camera to identify foreground and background regions, such that we can limit an effect to only the foreground or only the background. As prerequisites, we need a depth camera, such as Microsoft Kinect, and we need to build OpenCV with support for our depth camera. For build instructions, see Chapter 1, Setting up OpenCV.
OpenCV Computer Vision with Python
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OpenCV Computer Vision with Python
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Overview of this book
<p>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 how to efficiently process image data with NumPy and SciPy, then this book is for you.</p>
<p>This book has practical, project-based tutorials for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python. It is a 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.</p>
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Table of Contents (14 chapters)
OpenCV Computer Vision with Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Setting up OpenCV
Handling Files, Cameras, and GUIs
Filtering Images
Tracking Faces with Haar Cascades
Detecting Foreground/Background Regions and Depth
Integrating with Pygame
Generating Haar Cascades for Custom Targets
Index
Customer Reviews