Book Image

Complete Virtual Reality and Augmented Reality Development with Unity

By : Jesse Glover, Jonathan Linowes
Book Image

Complete Virtual Reality and Augmented Reality Development with Unity

By: Jesse Glover, Jonathan Linowes

Overview of this book

Unity is the leading platform to develop mixed reality experiences because it provides a great pipeline for working with 3D assets. Using a practical and project-based approach, this Learning Path educates you about the specifics of AR and VR development using Unity 2018 and Unity 3D. You’ll learn to integrate, animate, and overlay 3D objects on your camera feed, before moving on to implement sensor-based AR applications. You’ll explore various concepts by creating an AR application using Vuforia for both macOS and Windows for Android and iOS devices. Next, you’ll learn how to develop VR applications that can be experienced with devices, such as Oculus and Vive. You’ll also explore various tools for VR development: gaze-based versus hand controller input, world space UI canvases, locomotion and teleportation, timeline animation, and multiplayer networking. You’ll learn the Unity 3D game engine via the interactive Unity Editor and C# programming. By the end of this Learning Path, you’ll be fully equipped to develop rich, interactive mixed reality experiences using Unity. This Learning Path includes content from the following Packt products: • Unity Virtual Reality Projects - Second Edition by Jonathan Linowes • Unity 2018 Augmented Reality Projects by Jesse Glover
Table of Contents (24 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

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...