Book Image

OpenCV 3 Blueprints

By : Joseph Howse, Puttemans, Sinha
Book Image

OpenCV 3 Blueprints

By: Joseph Howse, Puttemans, Sinha

Overview of this book

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!
Table of Contents (9 chapters)
8
Index

Face detection and recognition


Most existing authentication systems start by detecting a face and trying to recognize it by matching it to a database of known people who use the system. This subsection will take a closer look at that. We will not dive into every single parameter of the software.

Note

If you want more information about complete face detection and the recognition pipeline for both people and cats, then take a look at one of the PacktPub books called OpenCV for Secret Agents. It looks at the complete process in more detail.

If you want a very detailed explanation of the parameters used for the face detection interface in OpenCV based on the cascade classification pipeline from Viola and Jones, then I suggest going to Chapter 5, Generic Object Detection for Industrial Applications, which discusses the interface generalized for generic object detection.

Whenever you are focusing on an authentication system, you want to make sure that you are familiar with the different sub-tasks...