Collaborative Augmented Reality (CAR) systems based on mobile phones have experienced a huge expansion last years, since the hardware features of most mobile phones provide excellent multimedia services and wireless network capabilities. In previous works, we improved the performance of large-scale CAR systems based on mobile phones that use fiducial marker tracking. However, CAR systems based on natural feature tracking have just emerged, changing the way in which Augmented Reality applications work. In this paper, we propose the performance evaluation of CAR systems based on feature tracking when using mobile phones, and their comparison with CAR systems based on fiducial marker tracking. The evaluation of the whole CAR system includes the rendering of the virtual environment with Unity3D. The purpose is to provide the reader with a reference about the performance that can be achieved with each kind of CAR system. The evaluation results of client devices show that they work faster with natural feature (commonly denoted as markerless) tracking than with fiducial marker tracking, regardless of the phone model and the operating system considered. The evaluation results of the whole CAR system show that natural feature tracking provides similar performance than fiducial marker tracking when the system reaches saturation. However, the use of natural feature tracking allows better performance for low workloads or when the system approaches saturation, since, it provides similar response times at the cost of increasing the percentage of CPU utilization in the server, instead of dropping messages. These results validate natural feature tracking as the best option for CAR systems based on mobile phones.
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This work has been jointly supported by the Spanish MICINN and the European Commission FEDER funds under grants TIN2009-14475-C04-04 and TIN2011-15734-E.
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Fernández, V., Orduña, J.M. & Morillo, P. Comparative performance evaluation of CAR systems based on mobile phones and feature tracking. J Supercomput 70, 552–563 (2014). https://doi.org/10.1007/s11227-013-1082-9
- Collaborative Augmented Reality
- Natural feature tracking
- Mobile phones