Online Multi-Object Thermal Tracking and Reidentification using YOLO and DeepSORT in Low Light Environment

Ricky Papudi, Septian Fahrezi, Aldy Sipahutar, Bryan Firjatullah, Nur Ibrahim, Benyamin Kusumoputro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Multi-object tracking and reidentification has been used in various domains such as surveillance, human-machine interface, and vehicle navigation. However, existing methods primarily rely on deep learning and tracking-by-detection (TBD) techniques using visible light cameras, which face challenges in low-light conditions. To address this, we propose a novel multi-object tracking approach utilizing thermal cameras to overcome visibility issues in such environments. Our method integrates the YOLOv7 for precise image detection and the DeepSORT algorithm for efficient tracking amidst occlusion and object similarities. Through rigorous experimentation, we achieved notable results, obtaining an IDF1 score of 0.911, F1 Score of 0.878, MOTA of 0.767, and MOTP of 0.161, underscoring the efficacy of our approach in multi-object tracking under challenging lighting conditions. Given the scarcity of publicly available thermal datasets, we curated a thermal reidentification dataset comprising 10,000 thermal images captured in diverse low-light settings. Our dataset includes various poses and perspectives to enhance model performance. We structure our study to present related works, detail our proposed methodology, and analyze experimental results, highlighting the efficacy of our approach in multi-object tracking under low-light conditions.

Original languageEnglish
Title of host publicationProceedings of the 2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages14-20
Number of pages7
ISBN (Electronic)9798350353464
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024 - Hybrid, Bali, Indonesia
Duration: 4 Jul 20246 Jul 2024

Publication series

NameProceedings of the 2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

Conference

Conference2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024
Country/TerritoryIndonesia
CityHybrid, Bali
Period4/07/246/07/24

Keywords

  • data augmentation
  • DeepSORT
  • low-light environments
  • Multi-object tracking
  • thermal
  • YOLOv7

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