OpenCV 3 Blueprints + code

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Название:OpenCV 3 Blueprints

Автор Joseph Howse et al

Издательство: PACKT

Год: 2015

Страниц: 382

Язык: English

Формат: epub, azw3, pdf, code

Размер: 7 Mb, 8 Mb, 13 M, 276 Mb

Expand your knowledge of computer vision by building amazing projects with OpenCV 3

About This Book

Build computer vision projects to capture high-quality image data, detect and track objects, process the actions of humans or animals, and much more

Discover practical and interesting innovations in computer vision while building atop a mature open-source library, OpenCV 3

Familiarize yourself with multiple approaches and theories wherever critical decisions need to be made

Who This Book Is For

This book is ideal for you if you aspire to build computer vision systems that are smarter, faster, more complex, and more practical than the competition. This is an advanced book intended for those who already have some experience in setting up an OpenCV development environment and building applications with OpenCV. You should be comfortable with computer vision concepts, object-oriented programming, graphics programming, IDEs, and the command line.

Table of Contents

1: Getting the Most out of Your Camera System

2: Photographing Nature and Wildlife with an Automated Camera

3: Recognizing Facial Expressions with Machine Learning

4: Panoramic Image Stitching Application Using Android Studio and NDK

5: Generic Object Detection for Industrial Applications

6: Efficient Person Identification Using Biometric Properties

7: Gyroscopic Video Stabilization

What You Will Learn

Select and configure camera systems to see invisible light, fast motion, and distant objects

Build a “camera trap”, as used by nature photographers, and process photos to create beautiful effects

Develop a facial expression recognition system with various feature extraction techniques and machine learning methods

Build a panorama Android application using the OpenCV stitching module in C++ with NDK support

Optimize your object detection model, make it rotation invariant, and apply scene-specific constraints to make it faster and more robust

Create a person identification and registration system based on biometric properties of that person, such as their fingerprint, iris, and face

Fuse data from videos and gyroscopes to stabilize videos shot from your mobile phone and create hyperlapse style videos

In Detail

Computer vision is becoming accessible to a large audience of software developers who can leverage mature libraries such as OpenCV. However, as they move beyond their first experiments in computer vision, developers may struggle to ensure that their solutions are sufficiently well optimized, well trained, robust, and adaptive in real-world conditions. With sufficient knowledge of OpenCV, these developers will have enough confidence to go about creating projects in the field of computer vision.

This book will help you tackle increasingly challenging computer vision problems that you may face in your careers. It makes use of OpenCV 3 to work around some interesting projects. Inside these pages, you will find practical and innovative approaches that are battle-tested in the authors’ industry experience and research. Each chapter covers the theory and practice of multiple complementary approaches so that you will be able to choose wisely in your future projects. You will also gain insights into the architecture and algorithms that underpin OpenCV’s functionality.

We begin by taking a critical look at inputs in order to decide which kinds of light, cameras, lenses, and image formats are best suited to a given purpose. We proceed to consider the finer aspects of computational photography as we build an automated camera to assist nature photographers. You will gain a deep understanding of some of the most widely applicable and reliable techniques in object detection, feature selection, tracking, and even biometric recognition. We will also build Android projects in which we explore the complexities of camera motion: first in panoramic image stitching and then in video stabilization.

By the end of the book, you will have a much richer understanding of imaging, motion, machine learning, and the architecture of computer vision libraries and applications!

Authors

Joseph Howse

Joseph Howse lives in Canada. During the cold winters, he grows a beard and his four cats grow thick coats of fur. He combs the cats every day. Sometimes, the cats pull his beard.

Joseph has been writing for Packt Publishing since 2012. His books include OpenCV for Secret Agents, OpenCV 3 Blueprints, Android Application Programming with OpenCV 3, Learning OpenCV 3 Computer Vision with Python, and Python Game Programming by Example.

When he is not writing books or grooming cats, Joseph provides consulting, training, and software development services through his company, Nummist Media (http://nummist.com).

Steven Puttemans

Steven Puttemans is a PhD research candidate at the KU Leuven, Department of Industrial Engineering Sciences. At this university, he is working for the EAVISE research group, which focuses on combining computer vision and artificial intelligence. He obtained a master of science degree in Electronics-ICT and further expanded his interest in computer vision by obtaining a master of science in artificial intelligence.

As an enthusiastic researcher, his goal is to combine state-of-the-art computer vision algorithms with real-life industrial problems to provide robust and complete object detection solutions for the industry. His previous projects include TOBCAT, an open source object detection framework for industrial object detection problems, and a variety of smaller computer vision-based industrial projects. During these projects, Steven worked closely with the industry.

Steven is also an active participant in the OpenCV community. He is a moderator of the OpenCV Q&A forum, and has submitted or reviewed many bug fixes and improvements for OpenCV 3. He also focuses on putting as much of his research as possible back into the framework to further support the open source spirit.

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