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

Authors: Ihsan Rabbi; Sehat Ullah; Muhammad Javed; Kartinah Zen

Addresses: Department of Computer Science and IT, University of Malakand, Lower Dir, Malakand Division, Khyber-Pakhtunkhwa, Pakistan; Institute of Engineering and Computing Sciences, University of Science and Technology, Bannu, Pakistan ' Department of Computer Science and IT, University of Malakand, Lower Dir, Malakand Division, Khyber-Pakhtunkhwa, Pakistan ' Institute of Engineering and Computing Sciences, University of Science and Technology, Bannu, Pakistan; Faculty of Computer Sciences and Information Technologies, University Malaysia Sarawak Kuching, Kota Samarahan, Sarawak, Malaysia ' Faculty of Computer Sciences and Information Technologies, University Malaysia Sarawak Kuching, Kota Samarahan, Sarawak, Malaysia

Abstract: 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.

Keywords: fiducial markers; augmented reality; ARToolKit; robust tracking; camera pose estimation; marker tracking.

DOI: 10.1504/IJCVR.2017.081238

International Journal of Computational Vision and Robotics, 2017 Vol.7 No.1/2, pp.68 - 82

Received: 03 Dec 2014
Accepted: 08 Apr 2015

Published online: 07 Dec 2016 *

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