Survey paper maps urban scene elements for road safety using computer vision

A new survey paper published on arXiv categorizes attention-worthy elements in urban street scenes to enhance road safety through computer vision. The paper proposes a taxonomy that divides critical traffic entities into anomalies and normal but critical elements, encompassing ten categories and twenty subclasses. It analyzes 35 vision-driven tasks and 73 datasets, highlighting their strengths and weaknesses to guide researchers and optimize resource allocation in the field. AI

IMPACT Provides a structured framework for computer vision research in road safety, identifying gaps and guiding future dataset development.

RANK_REASON This is a survey paper published on arXiv detailing a new taxonomy for urban street scene analysis using computer vision for road safety. [lever_c_demoted from research: ic=1 ai=1.0]

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• arXiv
• Yaoqi Huang

• paper
• safety

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