Review of Visual-infrared Cross-modal Person Re-identification Methods

FAN Huijie; YU Hang; ZHAO Yingchang; TANG Yandong

doi:10.13976/j.cnki.xk.2024.4041

Volume 54 Issue 1

Feb. 2025

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INFORMATION AND CONTROL > 2025 > 54(1): 50-65. > DOI: 10.13976/j.cnki.xk.2024.4041 CSTR: 32166.14.xk.2024.4041

FAN Huijie, YU Hang, ZHAO Yingchang, TANG Yandong. Review of Visual-infrared Cross-modal Person Re-identification Methods[J]. INFORMATION AND CONTROL, 2025, 54(1): 50-65. DOI: 10.13976/j.cnki.xk.2024.4041

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Review of Visual-infrared Cross-modal Person Re-identification Methods

FAN Huijie^1, ,,
YU Hang^{1, 2},
ZHAO Yingchang^{1, 3},
TANG Yandong¹

1.
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.
School of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China
3.
School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110158, China

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Received Date: February 01, 2024
Revised Date: August 25, 2024
Accepted Date: July 22, 2024

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Abstract

Abstract

Visible-infrared cross-modality person re-identification technology has garnered wide attention for its ability to provide round-the-clock monitoring regardless of nighttime conditions. We aim to help researchers find suitable solutions by analyzing existing methods, their applicable scenarios, and the advantages and disadvantages of different algorithms. Additionally, We seek to identify current challenges and explores future directions for visible-infrared cross-modality person re-identification. We first introduce the concept of person re-identification, review its development, and highlight the significance of visible-infrared cross-modality person re-identification. Subsequently, it categorizes research methods into basic methods, auxiliary model, unsupervised methods, and video-based approaches, analyzing their applicable scenarios, advantages, disadvantages, and potential future research directions. We also discuss current evaluation metrics and existing datasets for visible-infrared cross-modality person re-identification, analyzing the strengths and weaknesses of each dataset. Finally, We discuss the future prospects in this area.
- cross-modal person,
- re-identification,
- computer vision,
- unsupervised,
- auxiliary model

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References (117)

References

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