Mastering OpenCV 3 - Second Edition电子书

Title Page

Copyright

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

Cartoonifier and Skin Changer for Raspberry Pi

Accessing the webcam

Main camera processing loop for a desktop app

Generating a black and white sketch

Generating a color painting and a cartoon

Generating an evil mode using edge filters

Generating an alien mode using skin detection

Skin detection algorithm

Showing the user where to put their face

Implementation of the skin color changer

Summary

Exploring Structure from Motion Using OpenCV

Structure from Motion concepts

Estimating the camera motion from a pair of images

Point matching using rich feature descriptors

Finding camera matrices

Choosing the image pair to use first

Reconstructing the scene

Reconstruction from many views

Refinement of the reconstruction

Using the example code

Summary

References

Number Plate Recognition using SVM and Neural Network

Introduction to ANPR

ANPR algorithm

Plate detection

Segmentation

Classification

Plate recognition

OCR segmentation

Feature extraction

OCR classification

Evaluation

Summary

Non-Rigid Face Tracking

Overview

Utilities

Object-oriented design

Data collection - image and video annotation

Training data types

Annotation tool

Pre-annotated data (the MUCT dataset)

Geometrical constraints

Procrustes analysis

Linear shape models

A combined local-global representation

Training and visualization

Facial feature detectors

Correlation-based patch models

Learning discriminative patch models

Generative versus discriminative patch models

Accounting for global geometric transformations

Training and visualization

Face detection and initialization

Face tracking

Face tracker implementation

Training and visualization

Generic versus person-specific models

Summary

References

3D Head Pose Estimation Using AAM and POSIT

Active Appearance Models overview

Active Shape Models

Getting the feel of PCA

Triangulation

Triangle texture warping

Model Instantiation - playing with the AAM

AAM search and fitting

POSIT

Diving into POSIT

POSIT and head model

Tracking from webcam or video file

Summary

References

Face Recognition Using Eigenfaces or Fisherfaces

Introduction to face recognition and face detection

Step 1 - face detection

Implementing face detection using OpenCV

Loading a Haar or LBP detector for object or face detection

Accessing the webcam

Detecting an object using the Haar or LBP Classifier

Grayscale color conversion

Shrinking the camera image

Histogram equalization

Detecting the face

Step 2 - face preprocessing

Eye detection

Eye search regions

Geometrical transformation

Separate histogram equalization for left and right sides

Smoothing

Elliptical mask

Step 3 - Collecting faces and learning from them

Collecting preprocessed faces for training

Training the face recognition system from collected faces

Viewing the learned knowledge

Average face

Eigenvalues, Eigenfaces, and Fisherfaces

Step 4 - face recognition

Face identification - recognizing people from their face

Face verification - validating that it is the claimed person

Finishing touches - saving and loading files

Finishing touches - making a nice and interactive GUI

Drawing the GUI elements

Startup mode

Detection mode

Collection mode

Training mode

Recognition mode

Checking and handling mouse clicks

Summary

References