---
license: apache-2.0
tags:
- arxiv:2605.15779
- computer-vision
- object-tracking
- multi-camera
- uav
---
# Multi-Camera Multi-Vehicle Tracking System (UAV Dataset)
This dataset contains synchronized multi-UAV video footage and comprehensive tracking annotations, accompanying the paper **[A Topology-Aware Spatiotemporal Handover Framework for Continuous Multi-UAV Tracking](https://arxiv.org/abs/2605.15779)**.
It is designed for evaluating real-time multi-camera multi-vehicle tracking (MCMT) systems, focusing on solving trajectory fragmentation and maintaining global identity persistence across isolated UAV fields of view.
## Dataset Contents
### 1. Video Assets
Three synchronized 1-minute video clips captured from different UAV perspectives in complex urban environments.
- `uav1_1min.mp4`
- `uav2_1min.mp4`
- `uav3_1min.mp4`
Example: Consistent global tracking (e.g., the red car with ID 70) across overlapping UAV fields of view.
### 2. Annotations (CSVs)
The dataset includes structured CSV files with rich metadata generated by our tracking pipeline.
**Base Schema:**
```text
frame_index, x_min, y_min, x_max, y_max, class_id, confidence, tracker_id, global_id, camera_id, speed, status
```
*Note: Speed is estimated in km/h via pixel-to-meter scaling. Status tracks active/new_entry/exiting states.*
## Tracking Pipeline Code
The full production-ready pipeline (utilizing YOLO11, ByteTrack, and our Topology-based Spatiotemporal Handover mechanism) used to process these videos is open-source.
🔗 **[View Source Code on GitHub](https://www.google.com/search?q=https://github.com/JYe9/multi-camera-multi-vehicle-tracking-system)**
## Citation
If you find this dataset or our framework useful in your research, please cite our paper:
```bibtex
@misc{ye2026topologyaware,
title={A Topology-Aware Spatiotemporal Handover Framework for Continuous Multi-UAV Tracking},
author={Jianlin Ye and Christos Kyrkou and Panayiotis Kolios},
year={2026},
eprint={2605.15779},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```