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Improving Person Re-identification Through Low-Light Image Enhancement

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Pattern Recognition Applications and Methods (ICPRAM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14547))

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Abstract

Person re-identification (ReID) is a popular area of research in the field of computer vision. Despite the significant advancements achieved in recent years, most of the current methods rely on datasets containing subjects captured with good lighting under static conditions. ReID presents a significant challenge in real-world sporting scenarios, such as long-distance races that take place over varying lighting conditions, ranging from bright daylight to night-time. Unfortunately, increasing the exposure time on the capture devices to mitigate low-light environments is not a feasible solution, as it would result in blurry images due to the motion of the runners. This paper surveys several low-light image enhancement methods and finds that including an image pre-processing step in the ReID pipeline before extracting the distinctive body features of the subjects can lead to significant improvements in performance.

This work is partially funded by the ULPGC under project ULPGC2018-08, by the Spanish Ministry of Science and Innovation under project PID2021-122402OB-C22, and by the ACIISI-Gobierno de Canarias and European FEDER funds under projects ProID2020010024, ProID2021010012, ULPGC Facilities Net, and Grant EIS 2021 04.

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Acknowledgements

We would like to thank Arista Eventos SLU and Carlos Díaz Recio for granting us the use of Transgrancanaria media. We would also like to thank the volunteers and researchers who have taken part in the data collection and annotation, as well as the previous papers of this project.

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Authors and Affiliations

  1. SIANI, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Oliverio J. Santana, Javier Lorenzo-Navarro, David Freire-Obregón, Daniel Hernández-Sosa & Modesto Castrillón-Santana

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  1. Oliverio J. Santana
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  2. Javier Lorenzo-Navarro
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  3. David Freire-Obregón
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  4. Daniel Hernández-Sosa
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  5. Modesto Castrillón-Santana
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Correspondence to Oliverio J. Santana .

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Editors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Maria De Marsico

  2. ICAR-CNR, Napoli, Italy

    Gabriella Sanniti Di Baja

  3. University of Lisbon, Lisbon, Portugal

    Ana Fred

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Santana, O.J., Lorenzo-Navarro, J., Freire-Obregón, D., Hernández-Sosa, D., Castrillón-Santana, M. (2024). Improving Person Re-identification Through Low-Light Image Enhancement. In: De Marsico, M., Di Baja, G.S., Fred, A. (eds) Pattern Recognition Applications and Methods. ICPRAM 2023. Lecture Notes in Computer Science, vol 14547. Springer, Cham. https://doi.org/10.1007/978-3-031-54726-3_6

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  • DOI: https://doi.org/10.1007/978-3-031-54726-3_6

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