OSMO: Online Specific Models for Occlusion in Multiple Object Tracking under Surveillance Scene

Created by Xu Gao, Peking University

Introduction

OSMO is an online multi-object tracking framework which deals with two kinds of occlusion in the surveilalnce scene.

Citation

If you find OSMO useful in your research, please consider citing:

 @inproceedings{osmo2018,
    author = {Gao, Xu and Jiang, Tingting},
    title = {OSMO: Online Specific Models for Occlusion in Multiple Object Tracking Under Surveillance Scene},
    booktitle = {Proceedings of the 26th ACM International Conference on Multimedia},
    year = {2018},
    pages = {201--210},
}

Usage of the demo

Our project is written in Python 2.7 and PyTorch 0.2. Please set the environment at first.
Download the CampusStone dataset from https://drive.google.com/open?id=1nL60VdWkOkvjkdkAY53cuuLbV6wBStSn and unzip the file.
Download the code using "git clone https://github.com/gaoxu1024/OSMO.git".
Put the unziped dataset into ./dataset/.
For testing, use "sh osmo_run_list.sh".

We provide our tracking results in the folder ./result/. Besides, we only present the CampusStone dataset here currently, since other three datasets may have some private problems with the government.

References

[1] Xu Gao, and Tingting Jiang. OSMO: Online Specific Models for Occlusion in Multiple Object Tracking Under Surveillance Scene. Proceedings of the 26th ACM International Conference on Multimedia (MM), 2018.

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