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. 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! Style and approach This book covers a combination
of theory and practice. We examine blueprints for specific projects
and discuss the principles behind these blueprints, in detail.
General
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