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.

Afiliação

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 em En | MEDLINE | ID: mdl-35591139

Assuntos

Pedestres; Acidentes de Trânsito/prevenção & controle; Cidades; Humanos; Inteligência; Segurança; Caminhada

Palavras-chave

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

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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Pedestres Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article

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