Accelerating the Mass-Adoption of Augmented Reality through High-Fidelity Prototyping

So far, Augmented Reality (AR) systems have been confined to research prototypes and niche applications. However, recent advances in AR research make it seem feasible that AR can go beyond this stage. We envision that it can find broad adoption on consumer devices; therefore, ubiquitously enriching peoples’ life. It is very likely that mobile phones are going to be the first delivery platform of AR for the masses. They already include cameras (one of the preconditions for doing AR) and they are already being carried on a daily basis by many people. As a result, several research groups and companies have recently been focussing their efforts on this target platform. Most of the time, these efforts consist of porting existing AR applications and tracking algorithms to mobile phones. While this approach helps to make AR popular, we doubt that these efforts alone are sufficient for a mass-adoption of AR. In this paper, we present an alternative, complementary research strategy for achieving this goal. Fundamentally, current mobile phones have not been designed to run AR applications. Therefore, the user interfaces and applications that can run on them can achieve a low-fidelity only. As a result, it is inherently very difficult to create compelling user experiences on current mobile phones. We believe in a different approach: by simulating the capabilities of future, powerful mobile phones, we can create rich, high-fidelity user interfaces and applications. These explorations can help to convince mobile phone companies to create mobile phones with specialized AR hardware. As a result, the mass-adoption of AR would be accelerated. The rest of this paper is structured as follow: Section 2 presents a brief overview of tracking technology for AR, since tracking is the main technical constraint for running AR applications. Section 3 details the motivation and our plan for creating high-fidelity prototypes. Section 4 draws conclusions and details future work. 2. Tracking for AR