Book Image

Unity 2018 Augmented Reality Projects

By : Jesse Glover
Book Image

Unity 2018 Augmented Reality Projects

By: Jesse Glover

Overview of this book

Augmented Reality allows for radical innovations in countless areas. It magically blends the physical and virtual worlds, bringing applications from a screen into your hands. Meanwhile, Unity has now become the leading platform to develop augmented reality experiences, as it provides a great pipeline for working with 3D assets. Using a practical and project-based approach, Unity 2018 Augmented Reality Projects educates you about the specifics of augmented reality development in Unity 2018. This book teaches you how to use Unity in order to develop AR applications which can be experienced with devices such as HoloLens and Daydream. You will learn to integrate, animate, and overlay 3D objects on your camera feed, before gradually moving on to implementing sensor-based AR applications. In addition to this, you will explore the technical considerations that are especially important and possibly unique to AR. The projects in the book demonstrate how you can build a variety of AR experiences, whilst also giving insights into C# programming as well as the Unity 3D game engine via the interactive Unity Editor. By the end of the book, you will be equipped to develop rich, interactive augmented reality experiences for a range of AR devices and platforms using Unity.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
Packt Upsell

What is OpenCV?

OpenCV stands for Open Computer Vision. OpenCV is an open source computer vision and machine learning software library that was built with C++ and has C++, Python, Java, and Matlab interfaces to support Windows, Linux, Android, and macOS.

OpenCV mainly focuses on real-time vision applications, although it can be used for machine learning very nicely. The library has many optimized algorithms and functions to compose or support such algorithms for state-of-the-art computer vision and machine learning, with roughly 2,500. To break down the ratio here, there are roughly 500 algorithms, and the rest are functions to compose or support these algorithms.

Talking about algorithms is fun and all, but I’m sure you are more interested in knowing what these algorithms are capable of doing. The algorithms are designed to be used to detect faces, recognize faces, identify objects, detect and classify human actions in video feeds, track camera movements, move object tracking, extraction...