Book Image

OpenCV 3 Blueprints

By : Matthew John Macdonald, Jason Clemons, Gary Bradski, Alasdair McAndrew, Steven Puttemans, Joseph Howse, Utkarsh Sinha, Quan Hua
Book Image

OpenCV 3 Blueprints

By: Matthew John Macdonald, Jason Clemons, Gary Bradski, Alasdair McAndrew, Steven Puttemans, Joseph Howse, Utkarsh Sinha, Quan Hua

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Table of Contents (14 chapters)
OpenCV 3 Blueprints
OpenCV 3 Blueprints
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Getting the Most out of Your Camera System
Getting the Most out of Your Camera System
Coloring the light
Capturing the subject in the moment
Rounding up the unusual suspects
Supercharging the PlayStation Eye
Supercharging the ASUS Xtion PRO Live and other OpenNI-compliant depth cameras
Supercharging the GS3-U3-23S6M-C and other Point Grey Research cameras
Shopping for glass
Summary
2
Photographing Nature and Wildlife with an Automated Camera
Photographing Nature and Wildlife with an Automated Camera
Planning the camera trap
Controlling a photo camera with gPhoto2
Detecting the presence of a photogenic subject
Processing images to show subtle colors and motion
Further study
Summary
3
Recognizing Facial Expressions with Machine Learning
Recognizing Facial Expressions with Machine Learning
Introducing facial expression recognition
Finding the face region in the image
Feature extraction
Classification
Evaluation
System overview
Further reading
Summary
4
Panoramic Image Stitching Application Using Android Studio and NDK
Panoramic Image Stitching Application Using Android Studio and NDK
Introducing the concept of panorama
The Android section – an application user interface
Integrating OpenCV into the Android Studio
Application showcase
Further improvement
Summary
5
Generic Object Detection for Industrial Applications
Generic Object Detection for Industrial Applications
Difference between recognition, detection, and categorization
Smartly selecting and preparing application specific training data
Parameter selection when training an object model
Using scene specific knowledge and constraints to optimize the detection result
Obtaining rotation invariance object detection
2D scale space relation
Performance evaluation and GPU optimizations
Practical applications
Summary
6
Efficient Person Identification Using Biometric Properties
Efficient Person Identification Using Biometric Properties
Biometrics, a general approach
Face detection and recognition
Fingerprint identification, how is it done?
Iris identification, how is it done?
Combining the techniques to create an efficient people-registration system
Summary
7
Gyroscopic Video Stabilization
Gyroscopic Video Stabilization
Stabilization with images
Stabilization with hardware
A hybrid of hardware and software
The math
Project overview
Capturing data
Android specifics
Calibration
Rolling shutter compensation
What's next?
Summary
Index
Index

Summary

This chapter showed a complete panorama application in Android Studio where OpenCV 3 is used in both the Java interface and the C++ interface with the support of the Native Development Kit (NDK). The chapter also introduced us to how to use the Android Camera API with the OpenCV library. Also, the chapter illustrated some basic implementation with the OpenCV 3 stitching module to perform image stitching.

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