Vision-Based Pedestrian's Crossing Risky Behavior Extraction and Analysis for Intelligent Mobility Safety System.

Noh, Byeongjoon; Park, Hansaem; Lee, Sungju; Nam, Seung-Hee

Noh, Byeongjoon; Park, Hansaem; Lee, Sungju; Nam, Seung-Hee.

Afiliación

Noh B; Applied Science Research Institute, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseung-gu, Daejeon 34141, Korea.
Park H; Department of Civil and Environmental Engineering, Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseung-gu, Daejeon 34141, Korea.
Lee S; Department of Software, Sangmyung University, Cheonan 31066, Korea.
Nam SH; Center for Accelerator Research, Korea University, Sejong 30019, Korea.

Sensors (Basel) ; 22(9)2022 Apr 30.

Article en En | MEDLINE | ID: mdl-35591139

Asunto(s)

Peatones; Accidentes de Tránsito/prevención & control; Ciudades; Humanos; Inteligencia; Seguridad; Caminata

Palabras clave

computer vision; crossing behavior analysis; pedestrian safety; potential collision risks

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 2_ODS3 Problema de salud: 2_accidentes_transito Asunto principal: Peatones Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article

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