Book Image

Mastering OpenCV 4 - Third Edition

By : Roy Shilkrot, David Millán Escrivá
Book Image

Mastering OpenCV 4 - Third Edition

By: Roy Shilkrot, David Millán Escrivá

Overview of this book

Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.
Table of Contents (12 chapters)

Implementing SfM in OpenCV

OpenCV has an abundance of tools to implement a full-fledged SfM pipeline from first principles. However, such a task is very demanding and beyond the scope of this chapter. The former edition of this book presented just a small taste of what building such a system will entail, but luckily now we have at our disposal a tried and tested technique integrated right into OpenCV's API. Although the sfm module allows us to get away with simply providing a non-parametric function with a list of images to crunch and receive a fully reconstructed scene with a sparse point cloud and camera poses, we will not take that route. Instead, we will see in this section some useful methods that will allow us to have much more control over the reconstruction and exemplify some of the topics we discussed in the last section, as well as be more robust to noise.

This...