preprintJun 1, 2015GREEN OA

24/7 place recognition by view synthesis

Tokyo Institute of Technology · École Normale Supérieure · +2 more institutions

Indexed incrossref

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

533
total citations
FWCI
13.10
Percentile
100%
References
58
Citations per year

Authors

5

Topics & keywords

Keywords
  • Computer science
  • Matching (statistics)
  • Artificial intelligence
  • Representation (politics)
  • Scale (ratio)
  • Computer vision
  • Image (mathematics)
  • Principal (computer security)
UN Sustainable Development Goals
  • Sustainable cities and communities
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