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Intelligent Service Robotics
Erschienen in: Intelligent Service Robotics 4/2023

28.06.2023 | Original Research Paper

Night-to-day thermal image translation for deep thermal place recognition

verfasst von: Dong-Guw Lee, Hyeonjae Gil, Seungsang Yun, Jeongyun Kim, Ayoung Kim

Erschienen in: Intelligent Service Robotics | Ausgabe 4/2023

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Abstract

Place recognition PR is a fundamental task in autonomous robot systems that is still actively being researched. In recent years, CNN-based place recognition methods have surpassed classical methods. However, place recognition in the thermal infrared (TIR) image domain has shown poor performance when applied to both traditional and CNN-based methods due to the appearance variation of the same place throughout the day caused by varying temperature differences. In this paper, we propose a GAN-based nighttime to daytime thermal image translation model that translates thermal images captured at different times of the day into contrast-consistent and detail-preserving images, thus achieving time-agnostic thermal image representations. By applying our GAN-based models to input thermal images for place recognition tasks, we achieved a top-1 accuracy of 80.69% on the STHeReO dataset, outperforming other baseline methods.
Nächster Artikel Multi-UAV cooperative search and coverage control in post-disaster assessment: experimental implementation

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Metadaten
Titel
Night-to-day thermal image translation for deep thermal place recognition
verfasst von
Dong-Guw Lee
Hyeonjae Gil
Seungsang Yun
Jeongyun Kim
Ayoung Kim
Publikationsdatum
28.06.2023
Verlag
Springer Berlin Heidelberg
Erschienen in
Intelligent Service Robotics / Ausgabe 4/2023
Print ISSN: 1861-2776
Elektronische ISSN: 1861-2784
DOI
https://doi.org/10.1007/s11370-023-00473-7

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