SPLAT: Spherical Localization and Tracking in Large Spaces
SPLAT: Spherical Localization and Tracking in Large Spaces
复制标题
SPLAT：大空间中的球形定位和跟踪
DOI：
10.1109/vr46266.2020.1581313017497
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
T. Langlotz
中科院分区：
文献类型：
--
作者：
Lewis Baker;Jonathan Ventura;S. Zollmann;S. Mills;T. Langlotz
在实现增强现实（AR）界面时，必须跟踪摄像机运动，以便在用户的视图中精确地配准虚拟覆盖。然而，与大多数室内AR场景不同，在许多室外场景中，用户保持静态位置，主要执行旋转移动。通常用于解决跟踪问题的同时定位和映射（SLAM）方法需要显著的平移相机运动来可靠地执行。所需平移的大小与场景的大小成比例，这在诸如开放场所或体育场之类的大型环境中加剧了该问题。在本文中，我们提出了一种替代SLAM方法，它结合了球形结构从运动和一个强大的3D跟踪方法。通过仿真和真实的测试，与ORB SLAM2算法进行了比较，结果表明，该算法在大空间中的跟踪更加可靠，且由于采用了球面运动约束，计算更加简单。我们在体育场或其他开放环境中为现场体育赛事实现AR界面的背景下讨论了这个问题，但我们的技术可能的应用场景超出了范围，可以应用于许多户外环境中的手持AR。
When implementing an Augmented Reality (AR) interface, it is essential to track camera motion in order to precisely register the virtual overlay in the view of the user. However, unlike most indoor AR scenarios, in many outdoor scenarios the user maintains a static position performing mostly rotational movements. Simultaneous Localization and Mapping (SLAM) methods typically used to solve the tracking problem require significant translational camera motion to perform reliably. The magnitude of the required translation is proportional to the size of the scene, exacerbating this problem in large environments such as open places or stadiums. In this paper, we present an alternative SLAM method, which combines spherical Structure-from-Motion and a robust 3D tracking method. We compare our method to ORB SLAM2 in synthetic and real tests, and show that our method can track more reliably in large spaces, with simpler calculation due to the spherical motion constraint. We discuss this issue in the context of implementing an AR interface for live sport events in stadiums or other open environments, but possible application scenarios for our technique go beyond and can be applied to handheld AR in many outdoor environments.
影响因子：
7.8
作者：
Mur-Artal, Raul;Tardos, Juan D.
通讯作者：
Tardos, Juan D.