Mastering OpenCV 3 - Second Edition
Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Programming, C & C++, C++, Application Software
| Author: | Daniel Lelis Baggio, Shervin Emami, David Millan Escriva, Khvedchenia Ievgen, Jason Saragih, Roy Shilkrot | ISBN: | 9781786466563 |
| Publisher: | Packt Publishing | Publication: | April 28, 2017 |
| Imprint: | Packt Publishing | Language: | English |
| Author: | Daniel Lelis Baggio, Shervin Emami, David Millan Escriva, Khvedchenia Ievgen, Jason Saragih, Roy Shilkrot |
| ISBN: | 9781786466563 |
| Publisher: | Packt Publishing |
| Publication: | April 28, 2017 |
| Imprint: | Packt Publishing |
| Language: | English |
Practical Computer Vision Projects
About This Book
- Updated for OpenCV 3, this book covers new features that will help you unlock the full potential of OpenCV 3
- Written by a team of 7 experts, each chapter explores a new aspect of OpenCV to help you make amazing computer-vision aware applications
- Project-based approach with each chapter being a complete tutorial, showing you how to apply OpenCV to solve complete problems
Who This Book Is For
This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.
What You Will Learn
- Execute basic image processing operations and cartoonify an image
- Build an OpenCV project natively with Raspberry Pi and cross-compile it for Raspberry Pi.text
- Extend the natural feature tracking algorithm to support the tracking of multiple image targets on a video
- Use OpenCV 3's new 3D visualization framework to illustrate the 3D scene geometry
- Create an application for Automatic Number Plate Recognition (ANPR) using a support vector machine and Artificial Neural Networks
- Train and predict pattern-recognition algorithms to decide whether an image is a number plate
- Use POSIT for the six degrees of freedom head pose
- Train a face recognition database using deep learning and recognize faces from that database
In Detail
As we become more capable of handling data in every kind, we are becoming more reliant on visual input and what we can do with those self-driving cars, face recognition, and even augmented reality applications and games. This is all powered by Computer Vision.
This book will put you straight to work in creating powerful and unique computer vision applications. Each chapter is structured around a central project and deep dives into an important aspect of OpenCV such as facial recognition, image target tracking, making augmented reality applications, the 3D visualization framework, and machine learning. You'll learn how to make AI that can remember and use neural networks to help your applications learn.
By the end of the book, you will have created various working prototypes with the projects in the book and will be well versed with the new features of OpenCV3.
Style and approach
This book takes a project-based approach and helps you learn about the new features by putting them to work by implementing them in your own projects.
Practical Computer Vision Projects
About This Book
- Updated for OpenCV 3, this book covers new features that will help you unlock the full potential of OpenCV 3
- Written by a team of 7 experts, each chapter explores a new aspect of OpenCV to help you make amazing computer-vision aware applications
- Project-based approach with each chapter being a complete tutorial, showing you how to apply OpenCV to solve complete problems
Who This Book Is For
This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.
What You Will Learn
- Execute basic image processing operations and cartoonify an image
- Build an OpenCV project natively with Raspberry Pi and cross-compile it for Raspberry Pi.text
- Extend the natural feature tracking algorithm to support the tracking of multiple image targets on a video
- Use OpenCV 3's new 3D visualization framework to illustrate the 3D scene geometry
- Create an application for Automatic Number Plate Recognition (ANPR) using a support vector machine and Artificial Neural Networks
- Train and predict pattern-recognition algorithms to decide whether an image is a number plate
- Use POSIT for the six degrees of freedom head pose
- Train a face recognition database using deep learning and recognize faces from that database
In Detail
As we become more capable of handling data in every kind, we are becoming more reliant on visual input and what we can do with those self-driving cars, face recognition, and even augmented reality applications and games. This is all powered by Computer Vision.
This book will put you straight to work in creating powerful and unique computer vision applications. Each chapter is structured around a central project and deep dives into an important aspect of OpenCV such as facial recognition, image target tracking, making augmented reality applications, the 3D visualization framework, and machine learning. You'll learn how to make AI that can remember and use neural networks to help your applications learn.
By the end of the book, you will have created various working prototypes with the projects in the book and will be well versed with the new features of OpenCV3.
Style and approach
This book takes a project-based approach and helps you learn about the new features by putting them to work by implementing them in your own projects.
