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Learning OpenCV puts you right in the middle of the rapidly expanding field of computer vision.

Written by the creators of OpenCV, the widely used free open-source library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable AR applications, peripherals and robotics to interpret visual input from cameras, separate out the elements of the scene, and then make decisions based on that data.

Computer vision is a swiftly expanding field in technology these days, with applications invasively creeping everywhere. It is the backbone of gesture recognition, autonavigation, and security identification.

OpenCV provides an easy-to-use computer vision infrastructure along with a comprehensive library containing more than 500 functions that can run vision code in real time. With Learning OpenCV, any developer or hobbyist can get up and running with the framework basic quickly, whether it's to build simple or sophisticated vision applications. The book includes:

A thorough introduction to OpenCV
Getting input from cameras
Transforming images
Shape matching
Pattern recognition, including face detection
Segmenting images
Tracking and motion in 2 and 3 dimensions
Machine learning algorithms

Hands-on exercises at the end of each chapter help you absorb the concepts, and an appendix explains how to set up an OpenCV project in Visual Studio. OpenCV is written in performance optimised C/C++ code, runs on Windows, Linux, and Mac OS X, and is free for commercial and research use under a BSD license. Getting machines to see is a challenging but entertaining goal. If you're intrigued by the possibilities, Learning OpenCV gets you started on building computer vision applications of your own.

 

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