Augmented Reality Summer School
(Registration period has been expired)
February 11th - 15th, 2019
Auckland, New Zealand
Learn how to develop Empathic AR applications for the MagicLeap display.
Overview
Staff and students from the Empathic Computing Laboratory are organizing a week-long AR summer school at the University of Auckland from February 11th - 15th. The summer school will combine taught lectures with hands-on project work with the MagicLeap AR display and a variety of physiological sensors and input devices. Attendees will work in small groups to each complete an example MagicLeap project by the end of the week. This is a unique opportunity to learn how to develop MagicLeap applications from leading experts in the field.
Presenters
- Mark Billinghurst, University of Auckland
- Jimmy Baird, MagicLeap
- Amit Barde, University of Auckland
- Huidong Bai, University of Auckland
- Brian Jennings, MagicLeap
- Gun Lee, University of South Australia
- Aaron Quigley, University of St. Andrews
- Others to be announced..
Program
The summer school will combine 10-12 hours of lectures with 25-30 hours of hands-on development with the MagicLeap display. The tentative program is:
- Monday: Introduction to AR, UX/User Experience design for MagicLeap display, Developing ML applications with Unity, Project group formation
- Tuesday: Rapid prototyping for AR, Sensor systems for Empathic Computing, Interaction metaphors for AR, Using sensors in Unity, Project work
- Wednesday: AR content development, Perceptual issues in AR, Designing collaborative systems, Project work/review.
- Thursday: AR best practices, Evaluating AR systems, Project work
- Friday: Future research in AR, MagicLeap future directions, Project presentations
What You Will Learn
- An introduction to Augmented Reality and AR technology
- How to design good AR experiences
- How to use the Unity game engine
- How to program the ML-1 system using Unity
- Evaluation of AR experiences
- Principles of Empathic Computing
- Using physiological sensing in AR applications
- AR research directions