Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
Book Image

OpenCV Computer Vision Application Programming Cookbook Second Edition

By: Robert Laganiere

Overview of this book

OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.
Table of Contents (13 chapters)
12
Index

Matching images using a random sample consensus


When two cameras observe the same scene, they see the same elements but under different viewpoints. We have already studied the feature point matching problem in the previous chapter. In this recipe, we come back to this problem, and we will learn how to exploit the epipolar constraint between two views to match image features more reliably.

The principle that we will follow is simple: when we match feature points between two images, we only accept those matches that fall on the corresponding epipolar lines. However, to be able to check this condition, the fundamental matrix must be known, but we need good matches to estimate this matrix. This seems to be a chicken-and-egg problem. However, in this recipe, we propose a solution in which the fundamental matrix and a set of good matches will be jointly computed.

How to do it...

The objective is to be able to compute a fundamental matrix and a set of good matches between two views. To do so, all...