Abstract

The availability of powerful consumer-level smart devices and off-the-shelf software frameworks has tremendously popularized augmented reality (AR) applications. However, since the built-in cameras typically have rather limited field of view, it is usually preferable to position AR tools built upon these devices at a distance when large objects need to be tracked for augmentation. This arrangement makes it difficult or even impossible to physically interact with the augmented object. One solution is to adopt third person perspective (TPP) with which the smart device shows in real time the object to be interacted with, the AR information and the user herself, all captured by a remote camera. Through mental transformation between the user-centric coordinate space and the coordinate system of the remote camera, the user can directly interact with objects in the real world. To evaluate user performance under this cognitively demanding situation, we developed such an experimental TPP AR system and conducted experiments which required subjects to make markings on a whiteboard according to virtual marks displayed by the AR system. The same markings were also made manually with a ruler. We measured the precision of the markings as well as the time to accomplish the task. Our results show that although the AR approach was on average around half a centimeter less precise than the manual measurement, it was approximately three times as fast as the manual counterpart. Additionally, we also found that subjects could quickly adapt to the mental transformation between the two coordinate systems.

Highlights

  • Augmented reality (AR) combines the real world with computer-generated information in real-time

  • Observations in our experiment comprised the target positions marked by subjects and the time they took to mark those targets

  • These differences are highly significant, as the very low p-values (Tables 3 and 4) indicate and they were consistently observed in both experiments

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Summary

Introduction

Augmented reality (AR) combines the real world with computer-generated information in real-time. The virtual information is registered with related real objects to provide users with better understanding of those objects. The potentials of this new paradigm of visualizing and interacting with the actual surroundings have been enticing a large body of research and practice with regard to its applications. In Azuma’s influential survey paper [2], the application areas he reported covered only medicine, manufacture of complex machinery and military. Van Krevelen and Poelman [32] published an updated survey in 2010 and their work revealed that through these years AR applications had become more sophisticated in the traditional fields and spread widely into education, offices, personal information and entertainment. With the maturation of enabling technologies as well as the ensuing decrease of costs, barriers of adopting AR are being swept away and we can expect to see more reliable AR applications reaching a wider audience

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