基于orb -视觉测距定位估计和墙-地板边界图像配准的无标记室内/室外增强现实导航设备

Chian C. Ho, Ming-Che Ho, Chuan-Yu Chang
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引用次数: 5

摘要

对于无标记的室内/室外增强现实导航(ARN)技术,相机姿态必然是定位估计和姿态估计的基本参数,而地板平面是图像配准必不可少的基准目标。为了提高ARN的精度、可靠性和即时性,本文提出了orb -visual odometry定位估计和wall-floor-boundary图像配准。实验结果表明,与传统的ARN定位估计和图像配准方法相比,ORB-visual-odometry定位估计和墙-地板边界图像配准具有更高的精度和更小的延迟。另一方面,这两种方法在手持Android嵌入式平台上无缝实现,并顺利验证了在手持室内/室外增强现实导航设备上的良好运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Markerless Indoor/Outdoor Augmented Reality Navigation Device Based on ORB-Visual-Odometry Positioning Estimation and Wall-Floor-Boundary Image Registration
For markerless indoor/outdoor Augmented Reality Navigation (ARN) technology, camera pose is inevitably the fundamental argument of positioning estimation and pose estimation, and floor plane is indispensably the fiducial target of image registration. This paper proposes ORB-visual-odometry positioning estimation and wall-floor-boundary image registration to make ARN more precise, reliable, and instantaneous. Experimental results show both ORB-visual-odometry positioning estimation and wall-floor-boundary image registration have higher accuracy and less latency than conventional well-known positioning estimation and image registration methods for ARN. On the other hand, these proposed two methods are seamlessly implemented on the handheld Android embedded platform and are smoothly verified to work well on the handheld indoor/outdoor augmented reality navigation device.
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