August 26, 2025Scientific ReportsOpen Access

A two stage multi object tracking algorithm with transformer and attention mechanism

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Authors

MHMingxing HouTaiyuan Normal University YWYiming WuTongji University HSHong ShiFujian Medical University

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Implication

This algorithm integrates YOLOv8 and ByteTrack to improve tracking accuracy in environments with occlusion, suggesting a robust solution for real-time applications.

Key Points

The model achieved 80.5% Multiple Object Tracking Accuracy (MOTA) on the MOT17 dataset, showing significant performance improvements.
By combining YOLOv8 with an efficient vision transformer, the tracking model effectively addresses issues related to occlusion.
Utilizing a coordinate attention mechanism enhances feature extraction, reducing false positives and false negatives in detection.
The results indicate that the algorithm is effective for pedestrian tracking, highlighting its potential in engineering safety applications.

Cite This Study

Hou et al. (2025) studied this question.

synapsesocial.com/papers/68af63e3ad7bf08b1eae41a3 https://doi.org/10.1038/s41598-025-16389-4

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August 26, 2025Scientific ReportsOpen Access

A two stage multi object tracking algorithm with transformer and attention mechanism

View Full Paper

Ask AI

Bookmark

Authors

MHMingxing HouTaiyuan Normal University YWYiming WuTongji University HSHong ShiFujian Medical University

Discussion

Member takes

Implication

This algorithm integrates YOLOv8 and ByteTrack to improve tracking accuracy in environments with occlusion, suggesting a robust solution for real-time applications.

Key Points

The model achieved 80.5% Multiple Object Tracking Accuracy (MOTA) on the MOT17 dataset, showing significant performance improvements.
By combining YOLOv8 with an efficient vision transformer, the tracking model effectively addresses issues related to occlusion.
Utilizing a coordinate attention mechanism enhances feature extraction, reducing false positives and false negatives in detection.
The results indicate that the algorithm is effective for pedestrian tracking, highlighting its potential in engineering safety applications.

Cite This Study

Hou et al. (2025) studied this question.

synapsesocial.com/papers/68af63e3ad7bf08b1eae41a3 https://doi.org/10.1038/s41598-025-16389-4

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