Presented as a spotlight in BMVC22
Multiple Object Tracking from appearance by hierarchically clustering tracklets
Dataset | HOTA | DetA | AssA | MOTA | IDF1 |
---|---|---|---|---|---|
MOT17 | 62.6 | 62.2 | 63.4 | 76.7 | 77.7 |
MOT20 | 57.3 | 56.7 | 58.1 | 68.0 | 69.7 |
DanceTrack | 48.7 | 79.8 | 29.9 | 89.9 | 46.5 |
Code tested in python3.8
git clone https://github.com/NII-Satoh-Lab/MOT_FCG.git
cd $YOUR_PATH/MOT_FCG
pip install -r requirements.txt
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Download MOT17, MOT20, and DanceTrack.
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Download detections and feature data (around 20GB)
Note: This scripts downloads and prepares detections and features for MOT17, MOT20, and dancetrack. If you want to download only a specific dataset modify the below script.
bash scripts/prepare_data.sh
Run the code example for MOT17 using YOLOX and SBS features
python src/fcg_tracking.py --gt $YOUR_PATH_TO_DATASETS/MOT17Det --dataset mot17 --mode train --detector YOLOX --reid SBS --temp --iou --spatial --motion --w_tracklet 6 --w_fuse 3 --max_prop 40
Download evaluation repository from TrackEval
Download the git repository and follow the installation instructions and the ground truth data positioning.
git clone https://github.com/JonathonLuiten/TrackEval
python $TRACKEVAL_PATH/scripts/run_mot_challenge.py --TRACKERS_FOLDER $YOUR_PATH/MOT_FCG/results/mot17 --BENCHMARK MOT17 --TRACKERS_TO_EVAL fcg-YOLOX-SBS --GT_FOLDER $TRACKEVAL_PATH/data/MOT17 --SPLIT_TO_EVAL train --METRICS HOTA CLEAR Identity --PLOT_CURVES False --PRINT_CONFIG False --TIME_PROGRESS False
@inproceedings{Girbau_2022_BMVC,
author = {Andreu Girbau and Ferran Marques and Shin'ichi Satoh},
title = {Multiple Object Tracking from appearance by hierarchically clustering tracklets},
booktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022},
publisher = {{BMVA} Press},
year = {2022},
url = {https://bmvc2022.mpi-inf.mpg.de/0362.pdf}
}
- Code with our extracted detections + features
- Bibcitation
- Script to generate visualizations (e.g. videos)
- Scripts to generate low fps MOT17 videos