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  • Book Overview & Buying Mastering OpenCV 4
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Mastering OpenCV 4

Mastering OpenCV 4 - Third Edition

By : Roy Shilkrot, Millán Escrivá
2.7 (3)
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Mastering OpenCV 4

Mastering OpenCV 4

2.7 (3)
By: Roy Shilkrot, 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)
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Android Camera Calibration and AR Using the ArUco Module

Mobile devices running Google's Android outnumber all other mobile OSes and, in recent years, they have featured incredible computing power alongside high-quality cameras, which allows them to perform computer vision at the highest levels. One of the most sought after applications for mobile computer vision is augmented reality (AR). Blending real and virtual worlds has applications in entertainment and gaming, medicinel and healthcare, industry and defense, and many more. The world of mobile AR is advancing quickly, with new compelling demos popping up daily, and it is undeniably an engine for mobile hardware and software development. In this chapter, we will learn how to implement an AR application from scratch in the Android ecosystem, by using OpenCV's ArUco contrib module, Android's Camera2 APIs, as well...

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