research-article

GLAD: Global-Local-Alignment Descriptor for Pedestrian Retrieval

Authors:

Shiliang Zhang,

Qi TianAuthors Info & Claims

MM '17: Proceedings of the 25th ACM international conference on Multimedia

Pages 420 - 428

https://doi.org/10.1145/3123266.3123279

Published: 19 October 2017 Publication History

Abstract

The huge variance of human pose and the misalignment of detected human images significantly increase the difficulty of person Re-Identification (Re-ID). Moreover, efficient Re-ID systems are required to cope with the massive visual data being produced by video surveillance systems. Targeting to solve these problems, this work proposes a Global-Local-Alignment Descriptor (GLAD) and an efficient indexing and retrieval framework, respectively. GLAD explicitly leverages the local and global cues in human body to generate a discriminative and robust representation. It consists of part extraction and descriptor learning modules, where several part regions are first detected and then deep neural networks are designed for representation learning on both the local and global regions. A hierarchical indexing and retrieval framework is designed to eliminate the huge redundancy in the gallery set, and accelerate the online Re-ID procedure. Extensive experimental results show GLAD achieves competitive accuracy compared to the state-of-the-art methods. Our retrieval framework significantly accelerates the online Re-ID procedure without loss of accuracy. Therefore, this work has potential to work better on person Re-ID tasks in real scenarios.

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Cited By

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https://doi.org/10.1109/TNNLS.2022.3209537
Behera NSa PMuhammad KBakshi S(2025)Large-Scale Person Re-Identification for Crowd Monitoring in EmergencyIEEE Transactions on Automation Science and Engineering10.1109/TASE.2023.331800722(4691-4699)Online publication date: 2025
https://doi.org/10.1109/TASE.2023.3318007
Huang CLi WYang GYan JZhou BLi Y(2024)Cross-Video Pedestrian Tracking Algorithm with a Coordinate ConstraintSensors10.3390/s2403077924:3(779)Online publication date: 25-Jan-2024
https://doi.org/10.3390/s24030779
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Published In

cover image ACM Conferences

MM '17: Proceedings of the 25th ACM international conference on Multimedia

October 2017

2028 pages

ISBN:9781450349062

DOI:10.1145/3123266

General Chairs:
Qiong Liu
FXPAL, USA
,
Rainer Lienhart
Universität Augsburg, Germany
,
Haohong Wang
TCL America, USA
,
Program Chairs:
Sheng-Wei "Kuan-Ta" Chen
Academia Sinica, Taiwan
,
Susanne Boll
University of Oldenburg, Germany
,
Phoebe Chen
La Trobe University, Australia
,
Gerald Friedland
Lawrence Livermore National Lab, USA
,
Jia Li
Google, USA
,
Shuicheng Yan
Qihoo 360, China

Copyright © 2017 ACM.

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Association for Computing Machinery

New York, NY, United States

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Published: 19 October 2017

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National Science Foundation of China

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MM '17

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SIGMM

MM '17: ACM Multimedia Conference

October 23 - 27, 2017

California, Mountain View, USA

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MM '17 Paper Acceptance Rate 189 of 684 submissions, 28%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

Wang PSu FZhao ZZhao YBoulgouris N(2025)GAReID: Grouped and Attentive High-Order Representation Learning for Person Re-IdentificationIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.320953736:3(3990-4004)Online publication date: Mar-2025
https://doi.org/10.1109/TNNLS.2022.3209537
Behera NSa PMuhammad KBakshi S(2025)Large-Scale Person Re-Identification for Crowd Monitoring in EmergencyIEEE Transactions on Automation Science and Engineering10.1109/TASE.2023.331800722(4691-4699)Online publication date: 2025
https://doi.org/10.1109/TASE.2023.3318007
Huang CLi WYang GYan JZhou BLi Y(2024)Cross-Video Pedestrian Tracking Algorithm with a Coordinate ConstraintSensors10.3390/s2403077924:3(779)Online publication date: 25-Jan-2024
https://doi.org/10.3390/s24030779
Zhang YSong HWei J(2024)Cross-Domain Person Re-Identification Based on Feature Fusion InvarianceApplied Sciences10.3390/app1411464414:11(4644)Online publication date: 28-May-2024
https://doi.org/10.3390/app14114644
Yu MWang JYou RJi XLu W(2024)Multiple-local feature and attention fused person re-identification methodIntelligent Data Analysis10.3233/IDA-23039228:6(1679-1695)Online publication date: 15-Nov-2024
https://doi.org/10.3233/IDA-230392
Nikhal KMa YBhattacharyya SRiggan B(2024)HashReID: Dynamic Network with Binary Codes for Efficient Person Re-identification2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00594(6034-6043)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00594
Liu MWang FWang XWang YRoy-Chowdhury A(2024)A Two-Stage Noise-Tolerant Paradigm for Label Corrupted Person Re-IdentificationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.336149146:7(4944-4956)Online publication date: Jul-2024
https://doi.org/10.1109/TPAMI.2024.3361491
Yang XTian MLi MWei ZYuan LWang NGao X(2024)SSRR: Structural Semantic Representation Reconstruction for Visible-Infrared Person Re-IdentificationIEEE Transactions on Multimedia10.1109/TMM.2023.334785526(6273-6284)Online publication date: 2024
https://doi.org/10.1109/TMM.2023.3347855
Sarker PZhao QUddin M(2024)Transformer-Based Person Re-Identification: A Comprehensive ReviewIEEE Transactions on Intelligent Vehicles10.1109/TIV.2024.33506699:7(5222-5239)Online publication date: Jul-2024
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Cheng DTai HWang NFang CGao X(2024)Neighbor Consistency and Global-Local Interaction: A Novel Pseudo-Label Refinement Approach for Unsupervised Person Re-IdentificationIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.346503719(9070-9084)Online publication date: 2024
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