A Global Correction Framework for Camera Registration in Video See-Through Augmented Reality Systems
A Global Correction Framework for Camera Registration in Video See-Through Augmented Reality Systems
复制标题
视频透视增强现实系统中摄像机配准的全局校正框架
DOI：
10.1115/1.4063350
复制
发表时间：
2024
影响因子：
3.1
通讯作者：
Zhang, Yunbo
中科院分区：
文献类型：
--
作者：
Yang, Wenhao;Zhang, Yunbo
增强现实（AR）通过叠加计算机生成的虚拟图像来增强用户对真实环境的感知。这些虚拟图像提供了补充现实世界视图的附加视觉信息。 AR 系统在培训、维护、装配和机器人编程等各个制造领域迅速普及。在一些 AR 应用中，看不见的虚拟环境与物理环境精确对齐至关重要，以确保人类用户能够结合真实环境准确感知虚拟增强。实现这种精确对准的过程称为校准。在一些使用 AR 的机器人应用程序中，我们观察到指定工作空间内的视觉表示出现错位的情况。这种错位可能会影响机器人在执行任务期间操作的准确性。基于之前对 AR 辅助机器人编程系统的研究，这项工作调查了未对准误差的来源，并提出了一种简单有效的校准程序，以降低一般视频透视 AR 系统中的未对准精度。为了将虚拟信息准确地叠加到真实环境中，需要识别误差的来源和传播。在这项工作中，我们概述了每个点从虚拟世界空间到虚拟屏幕坐标的线性变换和投影。引入离线校准方法来确定从头戴式显示器 (HMD) 到相机的偏移矩阵，并进行实验来验证通过校准过程实现的改进。
Augmented reality (AR) enhances the user’s perception of the real environment by superimposing virtual images generated by computers. These virtual images provide additional visual information that complements the real-world view. AR systems are rapidly gaining popularity in various manufacturing fields such as training, maintenance, assembly, and robot programming. In some AR applications, it is crucial for the invisible virtual environment to be precisely aligned with the physical environment to ensure that human users can accurately perceive the virtual augmentation in conjunction with their real surroundings. The process of achieving this accurate alignment is known as calibration. During some robotics applications using AR, we observed instances of misalignment in the visual representation within the designated workspace. This misalignment can potentially impact the accuracy of the robot’s operations during the task. Based on the previous research on AR-assisted robot programming systems, this work investigates the sources of misalignment errors and presents a simple and efficient calibration procedure to reduce the misalignment accuracy in general video see-through AR systems. To accurately superimpose virtual information onto the real environment, it is necessary to identify the sources and propagation of errors. In this work, we outline the linear transformation and projection of each point from the virtual world space to the virtual screen coordinates. An offline calibration method is introduced to determine the offset matrix from the head-mounted display (HMD) to the camera, and experiments are conducted to validate the improvement achieved through the calibration process.