- eBook:Mastering OpenCV 4: A comprehensive guide to building computer vision and image processing applications with C++, 3rd Edition
- Author:Roy Shilkrot, David Millan Escriva
- Data:December 27, 2018
- Pages:280 pages
- Format:PDF, ePUB
- Learn about the new features that help unlock the full potential of OpenCV 4
- Build face detection applications with a cascade classifier using face landmarks
- Create an optical character recognition (OCR) model using deep learning and convolutional neural networks
Book DescriptionMastering 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.
What you will learn
- Build real-world computer vision problems with working OpenCV code samples
- Uncover best practices in engineering and maintaining OpenCV projects
- Explore algorithmic design approaches for complex computer vision tasks
- Work with OpenCV's most updated API (v4.0.0) through projects
- Understand 3D scene reconstruction and Structure from Motion (SfM)
- Study camera calibration and overlay AR using the ArUco Module
Who this book is forThis 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.
Chapter 2: Explore Structure from Motion with the SfM Module
Chapter 3: Face Landmark and Pose with the Face Module
Chapter 4: Number Plate Recognition with Deep Convolutional Networks
Chapter 5: Face Detection and Recognition with the DNN Module
Chapter 6: Introduction to Web Computer Vision with OpenCV.js
Chapter 7: Android Camera Calibration and AR Using the ArUco Module
Chapter 8: iOS Panoramas with the Stitching Module
Chapter 9: Finding the Best OpenCV Algorithm for the Job
Chapter 10: Avoiding Common Pitfalls in OpenCV