Automated detection of grade-crossing-trespassing near misses based on computer vision analysis of surveillance video data

Safety Science

Volumn 110, Issue , 2018, Pages 276-285

  Zhang, Zhipeng ^a   Trivedi, Chintan ^a   Liu, Xiang ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

Artificial intelligence; Grade crossing; Near miss; Safety; Video analytics

Indexed keywords

ACCIDENT PREVENTION; ARTIFICIAL INTELLIGENCE; RAILROAD ACCIDENTS; RAILROAD CROSSINGS; RAILROADS; RISK ANALYSIS; RISK ASSESSMENT; SECURITY SYSTEMS;

AUTOMATED DETECTION; GRADE CROSSING; GRADE-CROSSING ACCIDENTS; LIGHTING CONDITIONS; NEAR-MISSES; SAFETY IMPROVEMENT; SURVEILLANCE VIDEO; VIDEO ANALYTICS;

COMPUTER VISION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATION; CIRCADIAN RHYTHM; COMPUTER ANALYSIS; COMPUTER VISION ALGORITHM; HUMAN; ILLUMINATION; IMAGE PROCESSING; IMAGE QUALITY; MEASUREMENT ACCURACY; MOTION; MOTOR VEHICLE; NOISE; PRIORITY JOURNAL; PROBLEM SOLVING; SOCIAL PROBLEM; TRESPASSING; VALIDATION PROCESS; VIDEORECORDING;

EID: 85039445335     PISSN: 09257535     EISSN: 18791042     Source Type: Journal    
DOI: 10.1016/j.ssci.2017.11.023     Document Type: Article

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