Localization and tracking of stationary users for augmented reality
Localization and tracking of stationary users for augmented reality
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DOI：
10.1007/s00371-023-02777-2
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发表时间：
2023-02-02
期刊：
影响因子：
3.5
通讯作者：
Zollmann, Stefanie
中科院分区：
文献类型：
--
作者：
Baker, Lewis;Ventura, Jonathan;Zollmann, Stefanie
在增强现实应用中，必须知道用户的位置和取向以在用户的视场中正确地配准虚拟3D内容。为此，经常使用通过同时定位和映射（SLAM）的视觉跟踪。然而，当应用到经常发生的情况下，用户大多是固定的，在以前的研究中提出的许多方法有两个关键的限制。首先，SLAM技术本身不能解决相对于环境的先前模型的全局定位的问题。全球定位在许多应用中是必不可少的，其中多个用户预计将在共享空间内进行跟踪，例如体育赛事的观众。其次，这些方法通常假设显著的平移运动以从环境的局部模型准确地重建和跟踪，这对许多固定应用造成挑战。在本文中，我们扩展了最近的球形定位和跟踪的研究，以支持跟踪失败后的重新定位，以及在大型共享环境中的全球定位，并优化了操作方法的移动的硬件。我们还评估了各种最先进的定位方法，我们的视觉跟踪方法的鲁棒性，并证明了我们的系统在现实生活中的场景的有效性。
In augmented reality applications it is essential to know the position and orientation of the user to correctly register virtual 3D content in the user's field of view. For this purpose, visual tracking through simultaneous localization and mapping (SLAM) is often used. However, when applied to the commonly occurring situation where the users are mostly stationary, many methods presented in previous research have two key limitations. First, SLAM techniques alone do not address the problem of global localization with respect to prior models of the environment. Global localization is essential in many applications where multiple users are expected to track within a shared space, such as spectators at a sporting event. Secondly, these methods often assume significant translational movement to accurately reconstruct and track from a local model of the environment, causing challenges for many stationary applications. In this paper, we extend recent research on Spherical Localization and Tracking to support relocalization after tracking failure, as well as global localization in large shared environments, and optimize the method for operation on mobile hardware. We also evaluate various state-of-the-art localization approaches, the robustness of our visual tracking method, and demonstrate the effectiveness of our system in real-life scenarios.