OpenCV is very feature rich and provides multiple solutions and paths to resolve a visual-understanding problem. With this great power also comes hard work, choosing and crafting the best processing pipeline for the project requirements. Having multiple options means that probably finding the exact best performing solution is next to impossible, as many pieces are interchangeable and testing all the possible options is out of our reach. This problem's exponential complexity is compounded by the input data; more unknown variance in the incoming data will make our algorithm choices even more unstable. In other words, working with OpenCV, or any other computer vision library, is still a matter of experience and art. A priori intuition as to the success of one or another route to a solution is something computer vision engineers develop...
Mastering OpenCV 4 - Third Edition
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Mastering OpenCV 4 - Third Edition
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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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