E-Scooter Rider Detection and Classification in Dense Urban Environments. (arXiv:2205.10184v1 [cs.CV])

Accurate detection and classification of vulnerable road users is a safety
critical requirement for the deployment of autonomous vehicles in heterogeneous
traffic. Although similar in physical appearance to pedestrians, e-scooter
riders follow distinctly different characteristics of movement and can reach
speeds of up to 45kmph. The challenge of detecting e-scooter riders is
exacerbated in urban environments where the frequency of partial occlusion is
increased as riders navigate between vehicles, traffic infrastructure and other
road users. This can lead to the …

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