Mobile Augmented Reality

Research project at a glance

Augmented reality (AR) is concerned with the overlay of computer-generated imagery over real-world footage. The goal of the foreseen cooperation is to create a better understanding of perceptual and cognitive factors that affect in particular mobile AR systems, in order to improve these systems through novel interactive visualization techniques. There is neither an in-depth overview of these factors, nor well-founded knowledge on most effects as gained through formal validation. In particular long-term usage effects are badly understood.

Period

08.09.2015 to 08.09.2017

Project Leader

Project Description

Augmented reality (AR) is concerned with the overlay of computer-generated imagery over real-world footage. The goal of the foreseen cooperation is to create a better understanding of perceptual and cognitive factors that affect in particular mobile AR systems, in order to improve these systems through novel interactive visualization techniques.

There is neither an in-depth overview of these factors, nor well-founded knowledge on most effects as gained through formal validation. In particular long-term usage effects are badly understood. However, mobile platforms and emerging optical devices (“glasses”) ignite the number of users, as well as the system usage duration. To fulfill usability needs, a thorough understanding of perceptual and cognitive factors is highly needed by both research and industry: issues like depth misinterpretation, object relationship mismatches and information overload can severely limit usability of applications, or even pose risks on its usage. During the intended cooperation, a previously created overview of perceptual factors and effects (Kruijff et al, 2010) will be extended to create a solid research baseline. The current overview is based on a limited number of short-term validations, does not cover cognitive issues, and does no go in-depth. Through the performance of mid and longer-term validations, the extended classification of perceptual and cognitive factors and effects will reflect actual long-term usage of systems. Based on the gained knowledge, new interactive visualization techniques will be iteratively defined, developed and validated, optimized for the identified effects to create more usable applications.