24/7 place recognition by view synthesis
Tokyo Institute of Technology · École Normale Supérieure · +2 more institutions
Abstract
We address the problem of large-scale visual place recognition for situations where the scene undergoes a major change in appearance, for example, due to illumination (day/night), change of seasons, aging, or structural modifications over time such as buildings built or destroyed. Such situations represent a major challenge for current large-scale place recognition methods. This work has the following three principal contributions. First, we demonstrate that matching across large changes in the scene appearance becomes much easier when both the query image and the database image depict the scene from approximately the same viewpoint. Second, based on this observation, we develop a new place recognition…
Citation impact
- FWCI
- 13.10
- Percentile
- 100%
- References
- 58
Authors
5- ATAkihiko ToriiCorresponding
Tokyo Institute of Technology
- RARelja Arandjelović
École Normale Supérieure, Institut national de recherche en informatique et en automatique
- JŠJosef Šivic
École Normale Supérieure, Institut national de recherche en informatique et en automatique
- MOMasatoshi Okutomi
Tokyo Institute of Technology
- TPTomáš Pajdla
Czech Technical University in Prague
Topics & keywords
- Computer science
- Matching (statistics)
- Artificial intelligence
- Representation (politics)
- Scale (ratio)
- Computer vision
- Image (mathematics)
- Principal (computer security)
- Sustainable cities and communities