Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps
This work addresses the challenge of scalable and robust AR for users in urban environments, representing a novel method for a known bottleneck rather than an incremental improvement.
The authors tackled the problem of enabling city-scale shared augmented reality on mobile devices by developing an end-to-end production computer-vision system, which was deployed in San Francisco and mapped an area of several hundred kilometers.
In this paper we present the first published end-to-end production computer-vision system for powering city-scale shared augmented reality experiences on mobile devices. In doing so we propose a new formulation for an experience-based mapping framework as an effective solution to the key issues of city-scale SLAM scalability, robustness, map updates and all-time all-weather performance required by a production system. Furthermore, we propose an effective way of synchronising SLAM systems to deliver seamless real-time localisation of multiple edge devices at the same time. All this in the presence of network latency and bandwidth limitations. The resulting system is deployed and tested at scale in San Francisco where it delivers AR experiences in a mapped area of several hundred kilometers. To foster further development of this area we offer the data set to the public, constituting the largest of this kind to date.