Abstract
The process of modeling swarm behaviour based on natural phenomena usually involves the comparison to real world motion data. Our research focuses on analyzing and reproducing realistic behavior of self-organized traffic of motorbikes as it can be observed in some Asian metropoles such as Hanoi or Ho Chi Minh City. We introduce a semi-automatic method to extract motion trajectories of motorbikes in dense traffic situations from public video material. This technique can also be applied to other scenarios with a high density of entities that are only partialally visible on the video frame. To reconstruct these motions as trajectories on the ground plane, the camera pose is estimated using hints found in the videos. In addition we introduce a geometrical model for the locomotion of bikes which enables us to reconstruct the steering angle from the trajectories which gives more insight to the decision making process of the driver. A controlled experiment presented in this paper verifies the validity of our methods.
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Reh, B., Mombaur, K. (2016). Motion Reconstruction of Swarm-Like Self-organized Motor Bike Traffic from Public Videos. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2016. Lecture Notes in Computer Science(), vol 9882. Springer, Cham. https://doi.org/10.1007/978-3-319-44427-7_21
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DOI: https://doi.org/10.1007/978-3-319-44427-7_21
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