FOCUS detects object-level change in semi-static scenes where an object may be swapped in place for a similar-looking one. It fuses a geometric likelihood with an appearance likelihood rendered from a 3D Gaussian map, and a recursive three-state estimator tracks each object as PERSISTED, REPLACED or REMOVED. Rendering error is modelled probabilistically, with parameters calibrated from a change-free replay of the first mapping session; replacement F1 rises from 0.20 to 0.84 over a probabilistic baseline on a new Isaac Sim warehouse benchmark, and the method transfers to TorWIC without retuning.
Relevance
Calibrating from a change-free replay suits any map that has to run for months. Read with OASIS-Map for long-term autonomy and dynamic scenes.
Links
- arXiv
- Subfield: Semantic mapping, Mapping and localisation