7 research outputs found
Recent advances in video analytics for rail network surveillance for security, trespass and suicide prevention— a survey
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
Book of short Abstracts of the 11th International Symposium on Digital Earth
The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium
Primena inteligentnih sistema mašinske vizije autonomnog upravljanja železničkim vozilima
The railway is an important type of transport and has a significant
economic impact on the industry and people's everyday life. Due
to its capacities and complex infrastructure, it is necessary to work
on its constant development and improvement. Railway
automation requires the use of intelligent systems as a necessary
part of an autonomous railway vehicle. As from the point of view
of safe traffic, the existence of the object on the rail track and / or
in its vicinity represents a potential obstacle to the railway traffic,
and visibility has a very important role in correct and timely
detection of the object on the railway infrastructure, a key element
of autonomous railway vehicle is an obstacle detection system on
the part of the railway infrastructure, in conditions of reduced
visibility.
The subject of scientific research of this doctoral dissertation is the
application of intelligent machine vision systems in autonomous
train operation. For the purpose of detecting obstacles on the part
of the railway infrastructure in conditions of reduced visibility, a
thermal imaging camera and a night vision system are integrated
into the system, coupled with a developed advanced algorithm for
image processing with artificial intelligence tools. In addition, the
distance from the machine vision system to the detected object
was estimated. The operation of the system was tested in a series
of field experiments, at different locations, in different visibility
conditions and weather conditions, through realistic scenarios