Mastering OpenCV 3 - Second Edition

Practical Computer Vision Projects

Mastering OpenCV 3 - Second Edition

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Daniel Lélis Baggio et al.

Practical Computer Vision Projects
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Book Details

ISBN 139781786467171
Paperback250 pages

Book Description

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.

Table of Contents

Chapter 1: Cartoonifier and Skin Changer for Raspberry Pi
Accessing the webcam
Main camera processing loop for a desktop app
Implementation of the skin color changer
Chapter 2: Exploring Structure from Motion Using OpenCV
Structure from Motion concepts
Estimating the camera motion from a pair of images
Reconstructing the scene
Reconstruction from many views
Refinement of the reconstruction
Using the example code
Summary
References
Chapter 3: Number Plate Recognition using SVM and Neural Network
Introduction to ANPR
ANPR algorithm
Plate detection
Plate recognition
Summary
Chapter 4: Non-Rigid Face Tracking
Overview
Utilities
Geometrical constraints
Facial feature detectors
Face detection and initialization
Face tracking
Summary
References
Chapter 5: 3D Head Pose Estimation Using AAM and POSIT
Active Appearance Models overview
Active Shape Models
Model Instantiation - playing with the AAM
AAM search and fitting
POSIT
Summary
References
Chapter 6: Face Recognition Using Eigenfaces or Fisherfaces
Introduction to face recognition and face detection
Summary
References

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

Authors

Table of Contents

Chapter 1: Cartoonifier and Skin Changer for Raspberry Pi
Accessing the webcam
Main camera processing loop for a desktop app
Implementation of the skin color changer
Chapter 2: Exploring Structure from Motion Using OpenCV
Structure from Motion concepts
Estimating the camera motion from a pair of images
Reconstructing the scene
Reconstruction from many views
Refinement of the reconstruction
Using the example code
Summary
References
Chapter 3: Number Plate Recognition using SVM and Neural Network
Introduction to ANPR
ANPR algorithm
Plate detection
Plate recognition
Summary
Chapter 4: Non-Rigid Face Tracking
Overview
Utilities
Geometrical constraints
Facial feature detectors
Face detection and initialization
Face tracking
Summary
References
Chapter 5: 3D Head Pose Estimation Using AAM and POSIT
Active Appearance Models overview
Active Shape Models
Model Instantiation - playing with the AAM
AAM search and fitting
POSIT
Summary
References
Chapter 6: Face Recognition Using Eigenfaces or Fisherfaces
Introduction to face recognition and face detection
Summary
References

Book Details

ISBN 139781786467171
Paperback250 pages
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