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OpenCV 3 Computer Vision Application Programming Cookbook

OpenCV 3 Computer Vision Application Programming Cookbook

By : Robert Laganiere
3.5 (2)
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OpenCV 3 Computer Vision Application Programming Cookbook

OpenCV 3 Computer Vision Application Programming Cookbook

3.5 (2)
By: Robert Laganiere

Overview of this book

Making your applications see has never been easier with OpenCV. With it, you can teach your robot how to follow your cat, write a program to correctly identify the members of One Direction, or even help you find the right colors for your redecoration. OpenCV 3 Computer Vision Application Programming Cookbook Third Edition provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and exposed to important concepts in image and video analysis that will enable you to build your own computer vision applications. This book helps you to get started with the library, and shows you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. You will learn how to read and write images and manipulate their pixels. Different techniques for image enhancement and shape analysis will be presented. You will learn how to detect specific image features such as lines, circles or corners. You will be introduced to the concepts of mathematical morphology and image filtering. The most recent methods for image matching and object recognition are described, and you’ll discover how to process video from files or cameras, as well as how to detect and track moving objects. Techniques to achieve camera calibration and perform multiple-view analysis will also be explained. Finally, you’ll also get acquainted with recent approaches in machine learning and object classification.
Table of Contents (21 chapters)
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OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition
Credits
About the Author
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Preface

Computing the fundamental matrix of an image pair


The introductory section of this chapter presented the projective equation, describing how a scene point projects onto the image plane of a single camera. In this recipe, we will explore the projective relationship that exists between two images that display the same scene. These two images could have been obtained by moving a camera to two different locations to take pictures from two viewpoints, or by using two cameras, each of them taking a different picture of the scene. When those two cameras are separated by a rigid baseline, we use the term stereovision.

Getting ready

Let's now consider two pinhole cameras observing a given scene point, as shown in the following figure:

We learned that we can find the image x of a 3D point X by tracing a line joining this 3D point with the camera's center. Conversely, the scene point that has its image at position x on the image plane can be located anywhere on this line in the 3D space. This implies...

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