Recent Advances in Video Analytics for Rail Network Surveillance for Security, Trespass and Suicide Prevention-A Survey

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 12; p. 4324
• Main Authors: Zhang, Tianhao, Aftab, Waqas, Mihaylova, Lyudmila, Langran-Wheeler, Christian, Rigby, Samuel, Fletcher, David, Maddock, Steve, Bosworth, Garry
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01-06-2022; MDPI
• Subjects: Antiterrorism measures; Artificial intelligence; Closed circuit television; Computer vision; Electronic surveillance; Humans; image and video analytics; Machine learning; Machine vision; Methods; Prevention; Privacy; Public spaces; rail network systems; Railroads; Railway networks; Safety and security measures; Sensors; Static objects; Suicide; Suicide Prevention; Surveillance; Surveillance systems; Surveys and Questionnaires; Technology application; Television; Transportation networks; Trespass; Trespassing; United Kingdom; rail network systems; sensors; computer vision; image and video analytics; surveillance; machine learning; video anomaly detection
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22124324

Railway networks systems are by design open and accessible to people, but this presents challenges in the prevention of events such as terrorism, trespass, and suicide fatalities. With the rapid advancement of machine learning, numerous computer vision methods have been developed in closed-circuit television (CCTV) surveillance systems for the purposes of managing public spaces. These methods are built based on multiple types of sensors and are designed to automatically detect static objects and unexpected events, monitor people, and prevent potential dangers. This survey focuses on recently developed CCTV surveillance methods for rail networks, discusses the challenges they face, their advantages and disadvantages and a vision for future railway surveillance systems. State-of-the-art methods for object detection and behaviour recognition applied to rail network surveillance systems are introduced, and the ethics of handling personal data and the use of automated systems are also considered.