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VISION-BASED ROBUST CALIBRATION FOR OPTICAL SEE-THROUGH HEAD-MOUNTED DISPLAYS

机译:基于视觉的光透视头戴式显示器的鲁棒校准

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We propose Vision-based Robust Calibration (ViRC) method for OSTHMDs equipped with a camera. In the ViRC method, calibration parameters are decomposed into off-line parameters that remain constant relative to the positional relationship between the camera and the virtual screen, and on-line parameters related to the user's eye. Calculating the off-line parameters beforehand reduces the number of unknown parameters in the on-line phase, giving robust protection against the user's misalignments during calibration. In the off-line phase, the approximate position of the user's eye is calculated using the PnP algorithm. In the online phase, the actual position of the user's eye is estimated from the approximate one by non-linear minimization. In our experiments, we show that the ViRC method can decrease reprojection error by as much as 83% compared with the conventional method based on the DLT algorithm.
机译:我们提出了基于视觉的稳健校准(VIRC)方法,用于配备相机的OSPMD。在VIRC方法中,校准参数与相对于相机与虚拟屏幕之间的位置关系,以及与用户眼之间的在线参数保持恒定的离线参数。预先计算离线参数减少了在线阶段中未知参数的数量,在校准期间对用户的错位提供鲁棒保护。在离线阶段,使用PNP算法计算用户眼的近似位置。在在线阶段,通过非线性最小化从近似估计用户眼的实际位置。在我们的实验中,我们表明,与基于DLT算法的传统方法相比,VIRC方法可以将重注误差减少多达83%。

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