Learning Traffic Patterns at Intersections by Spectral Clustering of Motion Trajectories

@article{Atev2006LearningTP,
  title={Learning Traffic Patterns at Intersections by Spectral Clustering of Motion Trajectories},
  author={Stefan Atev and Osama Masoud and Nikolaos Papanikolopoulos},
  journal={2006 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2006},
  pages={4851-4856}
}
We address the problem of automatically learning the layout of a traffic intersection from trajectories of vehicles obtained by a vision tracking system. We present a similarity measure which is suitable for use with spectral clustering in problems that emphasize spatial distinctions between vehicle trajectories. The robustness of the method to small perturbations and its sensitivity to the choice of parameters are evaluated using real-world data 

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