Collaborative Large-Scale Dense 3D Reconstruction with Online Inter-Agent Pose Optimisation
Stuart Golodetz, Tommaso Cavallari, Nicholas A Lord, Victor A, Prisacariu, David W Murray, Philip H S Torr

TL;DR
This paper introduces a novel collaborative system enabling multiple users to efficiently reconstruct dense 3D models of entire buildings using consumer hardware, overcoming traditional hardware and time limitations.
Contribution
The system combines recent advances in real-time globally consistent reconstruction, visual-inertial odometry, and online relocalisation to facilitate large-scale collaborative 3D scene reconstruction.
Findings
Reconstructed entire house in under 30 minutes.
Achieved dense voxel-based models with consumer-grade hardware.
Enabled multi-user collaboration for large-scale scene capture.
Abstract
Reconstructing dense, volumetric models of real-world 3D scenes is important for many tasks, but capturing large scenes can take significant time, and the risk of transient changes to the scene goes up as the capture time increases. These are good reasons to want instead to capture several smaller sub-scenes that can be joined to make the whole scene. Achieving this has traditionally been difficult: joining sub-scenes that may never have been viewed from the same angle requires a high-quality camera relocaliser that can cope with novel poses, and tracking drift in each sub-scene can prevent them from being joined to make a consistent overall scene. Recent advances, however, have significantly improved our ability to capture medium-sized sub-scenes with little to no tracking drift: real-time globally consistent reconstruction systems can close loops and re-integrate the scene surface on…
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