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Quantification of error from system and environmental sources in Optical See-Through head mounted display calibration methods

机译:光学透视式头戴式显示器校准方法中来自系统和环境源的误差的量化

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A common problem with Optical See-Through (OST) Augmented Reality (AR) is misalignment or registration error with the amount of acceptable error being heavily dependent upon the type of application. Approximation methods, driven by user feedback, have been developed to estimate the necessary corrections for alignment errors. These calibration methods, however, are susceptable to induced error from system and environmental sources, such as human alignment error. The proposed research plan is intended to further the development of accurate and robust calibration methods for OST AR systems by quantifying the impact of specific factors shown to contribute to calibration error. An important aspect of this research will be to develop methods for examining each factor in isolation in order to determine the independent error contribution of each source. This will facilitate the establishment of acceptable thresholds for each type of error and be a meaningful step toward defining quality metrics for OST AR calibration techniques.
机译:光学透明(OST)增强现实(AR)的常见问题是未对准或配准误差,可接受误差的大小在很大程度上取决于应用程序的类型。已经开发了由用户反馈驱动的近似方法,以估计对准误差的必要校正。但是,这些校准方法容易受到来自系统和环境源的人为误差,例如人为对准误差。拟议的研究计划旨在通过量化表明会导致校准误差的特定因素的影响,来进一步开发针对OST AR系统的准确而强大的校准方法。这项研究的重要方面将是开发用于独立检查每个因素的方法,以确定每个来源的独立误差贡献。这将有助于为每种错误类型建立可接受的阈值,并且是朝着定义OST AR校准技术的质量指标的有意义的一步。

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