Paper Info
Title
SPLAT - Spherical Localization and Tracking in Large Spaces.
Abstract
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.
Year
DOI
Venue
2020
10.1109/VR46266.2020.1581313017497
VR
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
26
5
Name
Order
Citations
PageRank
Lewis Baker132.46
Jonathan Ventura222420.60
Stefanie Zollmann322722.58
Steven Mills44117.74
Tobias Langlotz539936.80