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 (18 chapters)
OpenCV Computer Vision Application Programming Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Describing keypoints with binary features


In the previous recipe, we learned how to describe a keypoint using rich descriptors extracted from the image intensity gradient. These descriptors are floating-point vectors that have a dimension of 64, 128, or sometimes even longer. This makes them costly to manipulate. In order to reduce the memory and computational load associated with these descriptors, the idea of using binary descriptors has been recently introduced. The challenge here is to make them easy to compute and yet keep them robust to scene and viewpoint changes. This recipe describes some of these binary descriptors. In particular, we will look at the ORB and BRISK descriptors for which we presented their associated feature point detectors in Chapter 8, Detecting Interest Points.

How to do it...

Owing to the nice generic interface on top of which the OpenCV detectors and the descriptors module are built, using a binary descriptor such as ORB is no different from using descriptors...