AHOR: Online Multi-Object Tracking With Authenticity Hierarchizing and Occlusion Recovery

Despite extensive exploration of more powerful multi-object tracking (MOT) frameworks, the impact of frequent occlusion has remained a formidable challenge. In this work, we present a novel MOT framework with Authenticity Hierarchizing and Occlusion Recovery (AHOR), that strikingly handles occlusion...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems for video technology 2024-09, Vol.34 (9), p.8253-8265
Main Authors: Jin, Haoyuan, Nie, Xuesong, Yan, Yunfeng, Chen, Xi, Zhu, Zhihang, Qi, Donglian
Format: Article
Language:English
Subjects:
Authenticity
Circuits and systems
Detectors
Electrical engineering
Feature extraction
Kalman filters
Multi-object tracking
Multiple target tracking
Occlusion
Recovery
Task analysis
Tracking
tracking-by-detection
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Summary:Despite extensive exploration of more powerful multi-object tracking (MOT) frameworks, the impact of frequent occlusion has remained a formidable challenge. In this work, we present a novel MOT framework with Authenticity Hierarchizing and Occlusion Recovery (AHOR), that strikingly handles occlusion and demonstrates superior precision and adaptability. Specifically, through an in-depth analysis of the classical tracking-by-detection (TBD) paradigm, we fully upgrade three aspects. Firstly, we propose an Existence Score that provides a more accurate depiction of detection authenticity under occlusion, enhancing the effectiveness and robustness of the hierarchical association. Secondly, we present an ingeniously devised pre-processing method in conjunction with a Recovery Intersection over Union (RIoU) for location similarity measurement, addressing the adverse effects of occlusion-induced disparity between visible and true object regions. Lastly, we introduce an Occluded Person Re-identification Module (ODReID) that extracts appearance features from the restricted visible region, overcoming the critical dependence on object quality. Results of extensive experiments demonstrate that our AHOR achieves state-of-the-art performance on MOT17, MOT20, DanceTrack, and VisDrone test sets.
ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2024.3392939