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Survey of Cross-Modal Person Re-Identification from a Mathematical Perspective

Author

Listed:
  • Minghui Liu

    (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China)

  • Yafei Zhang

    (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China)

  • Huafeng Li

    (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China)

Abstract

Person re-identification (Re-ID) aims to retrieve a particular pedestrian’s identification from a surveillance system consisting of non-overlapping cameras. In recent years, researchers have begun to focus on open-world person Re-ID tasks based on non-ideal situations. One of the most representative of these is cross-modal person Re-ID, which aims to match probe data with target data from different modalities. According to the modalities of probe and target data, we divided cross-modal person Re-ID into visible–infrared, visible–depth, visible–sketch, and visible–text person Re-ID. In cross-modal person Re-ID, the most challenging problem is the modal gap. According to the different methods of narrowing the modal gap, we classified the existing works into picture-based style conversion methods, feature-based modality-invariant embedding mapping methods, and modality-unrelated auxiliary information mining methods. In addition, by generalizing the aforementioned works, we find that although deep-learning-based models perform well, the black-box-like learning process makes these models less interpretable and generalized. Therefore, we attempted to interpret different cross-modal person Re-ID models from a mathematical perspective. Through the above work, we attempt to compensate for the lack of mathematical interpretation of models in previous person Re-ID reviews and hope that our work will bring new inspiration to researchers.

Suggested Citation

  • Minghui Liu & Yafei Zhang & Huafeng Li, 2023. "Survey of Cross-Modal Person Re-Identification from a Mathematical Perspective," Mathematics, MDPI, vol. 11(3), pages 1-25, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:654-:d:1049031
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    References listed on IDEAS

    as
    1. Coifman, Benjamin & Cassidy, Michael, 2002. "Vehicle reidentification and travel time measurement on congested freeways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(10), pages 899-917, December.
    2. Afshan Latif & Aqsa Rasheed & Umer Sajid & Jameel Ahmed & Nouman Ali & Naeem Iqbal Ratyal & Bushra Zafar & Saadat Hanif Dar & Muhammad Sajid & Tehmina Khalil, 2019. "Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-21, August.
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