Abstract
We present a system to conduct laboratory experiments with thousands of pedestrians. Each participant is equipped with an individual marker to enable us to perform precise tracking and identification. We propose a novel rotation invariant marker design which guarantees a minimal Hamming distance between all used codes. This increases the robustness of pedestrian identification. We present an algorithm to detect these markers, and to track them through a camera network. With our system we are able to capture the movement of the participants in great detail, resulting in precise trajectories for thousands of pedestrians. The acquired data is of great interest in the field of pedestrian dynamics. It can also potentially help to improve multi-target tracking approaches, by allowing better insights into the behaviour of crowds.
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Acknowledgements
This study was performed within the project BaSiGo (Bausteine für die Sicherheit von Großveranstaltungen, Safety and Security Modules for Large Public Events) funded by the Federal Ministry of Education and Research (BMBF) Program on “Research for Civil Security – Protecting and Saving Human Life”. Markus Mathias and Bastian Leibe are funded by the ERC Starting Grant Project CV-SUPER (ERC-2012-StG-307432).
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Mehner, W., Boltes, M., Mathias, M., Leibe, B. (2015). Robust Marker-Based Tracking for Measuring Crowd Dynamics. In: Nalpantidis, L., Krüger, V., Eklundh, JO., Gasteratos, A. (eds) Computer Vision Systems. ICVS 2015. Lecture Notes in Computer Science(), vol 9163. Springer, Cham. https://doi.org/10.1007/978-3-319-20904-3_40
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DOI: https://doi.org/10.1007/978-3-319-20904-3_40
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