Unsupervised pattern and outlier detection for pedestrian trajectories using diffusion maps
The movement of pedestrian crowds is studied both for real-world applications and to gain fundamental scientific insights into systems of self-driven particles. Trajectory data describes the dynamics of pedestrian crowds at the level of individual movement paths. Analysing such data is a central cha...
| Автори: | , , , |
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| Формат: | Journal article |
| Мова: | English |
| Опубліковано: |
Elsevier
2023
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