计算机科学
增强现实
人工智能
计算机视觉
人机交互
同时定位和映射
跟踪(教育)
混合现实
作者
Mark McGill,Jan Gugenheimer,Euan Freeman
出处
期刊:Virtual Reality Software and Technology
日期:2020-11-01
被引量:2
标识
DOI:10.1145/3385956.3418968
摘要
Current solutions for creating co-located Mixed Reality (MR) experiences typically rely on platform-specific synchronisation of spatial anchors or Simultaneous Localisation and Mapping (SLAM) data across clients, often coupled to cloud services. This introduces significant costs (in development and deployment), constraints (with interoperability across platforms often limited), and privacy concerns. For practitioners, support is needed for creating platform-agnostic co-located MR experiences. This paper explores the utility of aligned SLAM solutions by 1) surveying approaches toward aligning disparate device coordinate spaces, formalizing their theoretical accuracy and limitations; 2) providing skeleton implementations for audience-based, small-scale and large-scale co-location using said alignment approaches; and 3) detailing how we can assess the accuracy and safety of 6DoF/SLAM tracking solutions for any arbitrary device and dynamic environment without the need for an expensive ground truth optical tracking, by using trilateration and a $30 laser distance meter. Through this, we hope to further democratise the creation of cross-platform co-located MR experiences.
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