Iterative Prototyping of Urban CoBuilder: Tracking Methods and User Interface of an Outdoor Mobile Augmented Reality Tool for Co‐Designing

This research presents results from a study developing a smartphone app, UrbanCoBuilder, in which citizens can collaboratively create designs for urban environments usingaugmented reality technology and game mechanics. Eight prototypes were developed to refineselected design criteria, including tracking strategies, design elements, user experience and theinterface with game mechanics. The prototypes were developed through an iterative design processwith assessments and incremental improvements. The tracking was especially challenging andusing multiple bitonal markers combined with the smartphone’s gyroscope sensor to average theuser position was identified as the most suitable strategy. Still, portability and stability linked totracking need to be improved. Design elements, here building blocks with urban functions textures,were realistic enough to be recognizable and easy to understand for the users. Future studies willfocus on usability tests with larger user groups

FCSIT Research Bulletin 2017

The FCSIT Research Bulletin is an annual publication of the Faculty of Computer Science and Information Technology, UNIMAS. The purpose of FCSIT Research Bulletin is to disseminate information that represent the current state of the research activities, publications, research findings, training, conferences and seminar conducted by the academicians in the faculty

Analysing the attributes of fiducial markers for robust tracking in augmented reality applications

Tracking the position and orientation (pose) of camera is a critical challenge for different modern applications like augmented reality, robot navigation, robot localisation, and 3D modelling and surveillance systems. Marker-based tracking is the most active technique used for camera pose estimation. For the development of augmented reality applications different marker-based tracking toolkits are available that consists of specific set of fiducial markers. In this paper, various fiducial marker attributes are analysed that helps to increase the accuracy of marker-based tracking in augmented reality applications. Experimental modules are developed to calculate the optimal values for each attribute. The experiments are designed to analyse the marker size, distance between marker and camera, the marker speed along all axis, the environmental brightness, the lighting contrast in the environment and dependency of marker size on tracking distance. Experimental study shows that these attributes affect the marker tracking. Augmented reality researchers can use these findings for the development of more reliable and accurate application