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 videoprocessing 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 bidirectional flows of walkers. The extension builds on the computer vision library OpenCV.
Cite
CITATION STYLE
Procházka, J., & Olševičová, K. (2014). Data-driven pedestrian model: From OpenCV to NetLogo. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8733, 322–331. https://doi.org/10.1007/978-3-319-11289-3_33
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