This repository contains the legacy version of the evaluation toolkit for the Visual Object Tracking (VOT) challenge. The toolkit is a set of Matlab (Octave compatible) scripts, a documentation and a set of integration examples for different programming languages. A new toolkit, written in Python 3 is avalable here.
For more detailed informations consult the documentation available in the source or a compiled version of the documentation here. You can also subscribe to the VOT mailing list to receive news about challenges and important software updates or join our support form to ask questions.
- Luka Čehovin (lead developer)
- Tomáš Vojíř
- Alan Lukežič
- Georg Nebehay
- Heng Cherkeng
- Stefan Duffner
- Mario Maresca
- Klaus Haag
- Alessio Dore
- Alan Torres
- Rok Mandeljc
If you use this version of the VOT toolkit in your work, consider citing the following cover publication:
@article{vot-toolkit,
title = "A modular toolkit for visual tracking performance evaluation",
journal = "SoftwareX",
volume = "12",
pages = "100623",
year = "2020",
issn = "2352-7110",
doi = "https://doi.org/10.1016/j.softx.2020.100623",
url = "http://www.sciencedirect.com/science/article/pii/S2352711020303368",
author = "Luka {Čehovin Zajc}"
}
The evaluation toolkit code and the documentation is available under GPL 3 license. The tracker examples are available under various licenses.
If you have any further enquiries, question, or comments, please refer to the contact infromation link on the VOT homepage. If you would like to file a bug report or a feature request, use the Github issue tracker. The issue tracker is for toolkit issues only, if you have a problem with tracker integration or any other questions, please use our support forum.