Abstract
Our objective was to replicate the movement of real pedestrians in NetLogo agent-based model using the video recording of pedestrians as the source of reliable data. To achieve this, it was necessary to develop the video-processing extension for NetLogo. The paper presents the principles of video data transformation, the implementation of the extension and the experiment with a sample video stream that demonstrates the self-organization of bi-directional flows of walkers. The extension builds on the computer vision library OpenCV.
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Procházka, J., Olševičová, K. (2014). Data-Driven Pedestrian Model: From OpenCV to NetLogo. In: Hwang, D., Jung, J.J., Nguyen, NT. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2014. Lecture Notes in Computer Science(), vol 8733. Springer, Cham. https://doi.org/10.1007/978-3-319-11289-3_33
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DOI: https://doi.org/10.1007/978-3-319-11289-3_33
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11288-6
Online ISBN: 978-3-319-11289-3
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