User Friendly Calibration for Tracking of Optical Stereo See-Through Head Worn Displays for Augmented Reality

F. Bernard, T. Engelke, Arjan Kuijper
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引用次数: 1

Abstract

In recent time devices like Google Glass and Oculus Rift gained a lot of public attention. So the field of Virtual and Augmented Reality has become a more and more attractive field of study. Optical Stereo See-Through Head Worn Displays (OST-HWD or OST-HMD) can be used for Augmented Reality, but have to be calibrated. This means, that one has to find a configuration, that aligns the image shown on the displays with the environment, which is observed by the built-in camera. If this is not done, the augmented virtual image would not align with the real world. In this paper, the process of this calibration approach is divided into two stages, hardware and user calibration, but with less constraints for the positions of the cameras, which makes it easier to use. We aim at a more user friendly suite for the calibration of OST-HWD devices. Therefore both of the aforementioned stages are combined in a new quick step-by-step installation wizard, which is written in HTML and JavaScript to ensure easy usability. We apply a new minimization model in order to simplify and robustify the calculations of the virtual plane. In addition to that the required hardware components, including camera and calibration rig, were simplified. The implemented software has been evaluated for its results of the computed virtual plane, intrinsic data and eye positions of the user. Finally a user study was conducted to rate the usability of the calibration process.
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用于增强现实的光学立体透视头戴式显示器跟踪的用户友好校准
最近,像谷歌眼镜和Oculus Rift这样的设备获得了很多公众的关注。因此,虚拟与增强现实领域已成为一个越来越有吸引力的研究领域。光学立体透视头戴式显示器(OST-HWD或OST-HMD)可用于增强现实,但必须进行校准。这意味着,人们必须找到一种配置,使显示器上显示的图像与环境保持一致,这是由内置摄像头观察到的。如果不这样做,增强的虚拟图像将与现实世界不一致。本文将该方法的标定过程分为硬件标定和用户标定两个阶段,但对摄像机位置的限制较少,便于使用。我们的目标是为OST-HWD设备的校准提供更友好的用户套件。因此,前面提到的两个阶段结合在一个新的快速分步安装向导中,该向导是用HTML和JavaScript编写的,以确保易于使用。为了简化和增强虚平面的计算,我们采用了一种新的最小化模型。此外,还简化了所需的硬件组件,包括相机和校准平台。所实现的软件对计算的虚拟平面、内在数据和用户眼睛位置的结果进行了评估。最后进行了一项用户研究,以评估校准过程的可用性。
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