OpenCV 3 Blueprints
Expand your knowledge of computer vision by building amazing projects with OpenCV 3
Published on 13. January 2025
382 pages
978-1-78439-142-3 (ISBN)
Description
Expand your knowledge of computer vision by building amazing projects with OpenCV
Key Features
Book DescriptionComputer 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!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
Who this book is for
Key Features
Book DescriptionComputer 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!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
Who this book is for
More details
Edition
Digital original
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
9,38 MB
ISBN-13
978-1-78439-142-3 (9781784391423)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Joseph Howse | Steven Puttemans | Quan Hua
OpenCV 3 Blueprints
Book
11/2015
Packt Publishing
€56.70
Shipment within 3-4 weeks
Persons
Joseph Howse lives in a Canadian fishing village, where he chats with his cats, crafts his books, and nurtures an orchard of hardy fruit trees. He is President of Nummist Media Corporation, which exists to support his books and to provide mentoring and consulting services, with a specialty in computer vision. On average, in 2015-2022, Joseph has written 1.4 new books or new editions per year for Packt. He also writes fiction, including an upcoming novel about the lives of a group of young people in the last days of the Soviet Union. 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. More info about Steven's research, projects, and interests can be found at https://stevenputtemans.github.io. Utkarsh Sinha lives in Pittsburgh, Pennsylvania, where he is pursuing a master's in computer vision at Carnegie Mellon University. He intends to learn the state of the art of computer vision at the university and work on real-life industrial scale computer vision challenges. Before joining CMU, he worked as a Technical Director at Dreamworks Animation on movies such as Home, How to Train your Dragon 2, and Madagascar 3. His work spans multiple movies and multiple generations of graphics technology. He earned his bachelor of engineering degree in computer science and his master of science degree in mathematics from BITS-Pilani, Goa. He has been working in the field of computer vision for about 6 years as a consultant and as a software engineer at start-ups. He blogs at http://utkarshsinha.com/ about various topics in technologymost of which revolve around computer vision. He also publishes computer vision tutorials on the Internet through his website, AI Shack (http://aishack.in/). His articles help people understand concepts in computer vision every day.
Content
Table of Contents
"Optimizing the pipeline: Efficient patterns for image capture processing and rendering"
"Photographing nature and wildlife with an automated camera"
Facial Expression with ml module
Panorama application in Android Studio with NDK
"Generic object detection for industrial applications"
"Efficient person identification"
"Gyroscopic image stabilization"
"Optimizing the pipeline: Efficient patterns for image capture processing and rendering"
"Photographing nature and wildlife with an automated camera"
Facial Expression with ml module
Panorama application in Android Studio with NDK
"Generic object detection for industrial applications"
"Efficient person identification"
"Gyroscopic image stabilization"
