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Visible-infrared Person Re-identification with Human Body Parts Assistance

Authors:

Yongjian LiuAuthors Info & Claims

ICMR '21: Proceedings of the 2021 International Conference on Multimedia Retrieval

Pages 631 - 637

https://doi.org/10.1145/3460426.3463671

Published: 01 September 2021 Publication History

Abstract

Person re-identification (re-id) has received ever-increasing research focus, because of its important role in video surveillance applications. This paper addresses the re-id problem between visible images of color cameras and infrared images of infrared cameras, which is significant in case that the appearance information is insufficient in poor illumination conditions. In this field, there are two key challenges, i.e., the difficulty to locate the discriminative information to re-identify the same person between visible and infrared images, and the difficulty to learn a robust metric for such large-scale cross-modality retrieval. In this paper, we propose a novel human body parts assistance network (BANet) to tackle the two challenges above. BANet mainly focuses on extracting discriminative information and learning robust features by leveraging the human body part cues. Extensive experiments demonstrate that the proposed approach outperforms the baseline and the state-of-the-art methods.

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Cited By

Uddin MBhuiyan ABappee FIslam MHasan M(2023)Person Re-Identification with RGB–D and RGB–IR Sensors: A Comprehensive SurveySensors10.3390/s2303150423:3(1504)Online publication date: 29-Jan-2023
https://doi.org/10.3390/s23031504
Song KZhao YHuang LYan YMeng Q(2023)RGB-T image analysis technology and applicationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.105919120:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.105919
Zheng HZhong XHuang WJiang KLiu WWang Z(2022)Visible-Infrared Person Re-Identification: A Comprehensive Survey and a New SettingElectronics10.3390/electronics1103045411:3(454)Online publication date: 3-Feb-2022
https://doi.org/10.3390/electronics11030454

Index Terms

Visible-infrared Person Re-identification with Human Body Parts Assistance
1. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Multimedia and multimodal retrieval
        Image search

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Abstract
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Information & Contributors

Information

Published In

cover image ACM Conferences

ICMR '21: Proceedings of the 2021 International Conference on Multimedia Retrieval

August 2021

715 pages

ISBN:9781450384636

DOI:10.1145/3460426

General Chairs:
Wen-Huang Cheng
National Yang Ming Chiao Tung University, Taiwan
,
Mohan Kankanhalli
National University of Singapore, Singapore
,
Meng Wang
Hefei University of Technology, China
,
Program Chairs:
Wei-Ta Chu
National Cheng Kung University, Taiwan
,
Jiaying Liu
Peking University, China
,
Marcel Worring
University of Amsterdam, Netherlands

Copyright © 2021 ACM.

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2021

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Fundamental Research Funds for the Central Universities

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ICMR '21

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SIGMM

ICMR '21: International Conference on Multimedia Retrieval

August 21 - 24, 2021

Taipei, Taiwan

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Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

Uddin MBhuiyan ABappee FIslam MHasan M(2023)Person Re-Identification with RGB–D and RGB–IR Sensors: A Comprehensive SurveySensors10.3390/s2303150423:3(1504)Online publication date: 29-Jan-2023
https://doi.org/10.3390/s23031504
Song KZhao YHuang LYan YMeng Q(2023)RGB-T image analysis technology and applicationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.105919120:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.105919
Zheng HZhong XHuang WJiang KLiu WWang Z(2022)Visible-Infrared Person Re-Identification: A Comprehensive Survey and a New SettingElectronics10.3390/electronics1103045411:3(454)Online publication date: 3-Feb-2022
https://doi.org/10.3390/electronics11030454

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