Structure from motion (SfM) is the process of recovering both the positions of cameras looking at a scene, and the sparse geometry of the scene. The motion between the cameras imposes geometric constraints that can help us recover the structure of objects, hence why the process is called SfM. Since OpenCV v3.0+, a contributed ("contrib") module called sfm was added, which assists in performing end-to-end SfM processing from multiple images. In this chapter, we will learn how to use the SfM module to reconstruct a scene to a sparse point cloud, including camera poses. Later, we will also densify the point cloud, adding many more points to it to make it dense by using an open Multi-View Stereo (MVS) package called OpenMVS. SfM is used for high-quality three-dimensional scanning, visual odometry for autonomous navigation...
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Table Of Contents
Mastering OpenCV 4 - Third Edition
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Mastering OpenCV 4
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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)
Preface
Free Chapter
Cartoonifier and Skin Color Analysis on the RaspberryPi
Explore Structure from Motion with the SfM Module
Face Landmark and Pose with the Face Module
Number Plate Recognition with Deep Convolutional Networks
Face Detection and Recognition with the DNN Module
Introduction to Web Computer Vision with OpenCV.js
Android Camera Calibration and AR Using the ArUco Module
iOS Panoramas with the Stitching Module
Finding the Best OpenCV Algorithm for the Job
Avoiding Common Pitfalls in OpenCV
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