A hybrid pose tracking approach for handheld augmented reality

Juan Li, Maarten Slembrouck, Francis Deboeverie, A. Bernardos, J. Besada, P. Veelaert, H. Aghajan, W. Philips, J. Casar
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引用次数: 10

Abstract

With the rapid advances in mobile computing, handheld Augmented Reality draws increasing attention. Pose tracking of handheld devices is of fundamental importance to register virtual information with the real world and is still a crucial challenge. In this paper, we present a low-cost, accurate and robust approach combining fiducial tracking and inertial sensors for handheld pose tracking. Two LEDs are used as fiducial markers to indicate the position of the handheld device. They are detected by an adaptive thresholding method which is robust to illumination changes, and then tracked by a Kalman filter. By combining inclination information provided by the on-device accelerometer, 6 degree-of-freedom (DoF) pose is estimated. Handheld devices are freed from computer vision processing, leaving most computing power available for applications. When one LED is occluded, the system is still able to recover the 6-DoF pose. Performance evaluation of the proposed tracking approach is carried out by comparing with the ground truth data generated by the state-of-the-art commercial motion tracking system OptiTrack. Experimental results show that the proposed system has achieved an accuracy of 1.77 cm in position estimation and 4.15 degrees in orientation estimation.
手持增强现实的混合姿态跟踪方法
随着移动计算技术的飞速发展,手持增强现实技术越来越受到人们的关注。手持设备的姿态跟踪对虚拟信息与现实世界的匹配至关重要,仍然是一个关键的挑战。在本文中,我们提出了一种结合基准跟踪和惯性传感器的低成本、精确和鲁棒的手持姿态跟踪方法。两个led用作基准标记,以指示手持设备的位置。采用对光照变化具有较强鲁棒性的自适应阈值法进行检测,然后采用卡尔曼滤波进行跟踪。通过结合设备上加速度计提供的倾角信息,估计出6个自由度(DoF)姿态。手持设备从计算机视觉处理中解放出来,将大部分计算能力留给应用程序。当一个LED被遮挡时,系统仍然能够恢复6自由度姿势。通过与最先进的商业运动跟踪系统OptiTrack生成的地面真实数据进行比较,对所提出的跟踪方法进行了性能评估。实验结果表明,该系统的位置估计精度为1.77 cm,方向估计精度为4.15°。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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