A Video-Based Object Detection System for Improving Safety at Level Crossings

Fakhfakh, Nizar; Khoudour, Louahdi; El-Koursi, El-Miloudi; Jacot, Jacques; Dufaux, Alain

doi:10.2174/1874447801105010045

Cited by 14 publications

(15 citation statements)

References 19 publications

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“…However, the system is unable to detect an object, which is inert or produce the same radiation as the background scene. 19 Another technique mentioned in literature 12,15 is ultrasonic detectors and Optical Beam method. The ultrasonic detectors use the transmission of an ultrasonic pulse and find the difference between transmitted and reflected pulse to detect the presence of moving or stationary object.…”

Section: Obstacle Detection Sensorsmentioning

confidence: 99%

A review of the technological developments for interlocking at level crossing

Fayyaz

Alexoulis-Chrysovergis

Southgate

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part F:

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A Level Crossing remains as one of the highest risk assets within the railway system often depending on the unpredictable behaviour of road and footpath users. For this purpose, interlocking through automated safety systems remains a key area for investigation. Within Europe, 2015–2016, 469 accidents at crossings were recorded of which 288 lead to fatalities and 264 lead to injuries. The European Union’s Agency for Railways has reported that Level Crossing fatalities account for just under 28% of all railway fatalities. This paper identifies suitable obstacle detection technologies and their associated algorithms that can be used to support risk reduction and management of Level Crossings. Furthermore, assessment and decision methods are presented to support their application. Finally state of the art and synergistic opportunity of which a combination of obstacle detection sensors with intelligent decisions layers such as Deep Learning are discussed which can provide robust interlocking decisions for rail applications. The sensor fusion of video camera and RADAR is a promising solution for Level Crossings. By applying additional sensing techniques such as RADAR imaging, further capabilities are added to the system, which can lead to a more robust approach.

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Section: Obstacle Detection Sensorsmentioning

confidence: 99%

A review of the technological developments for interlocking at level crossing

Fayyaz

Alexoulis-Chrysovergis

Southgate

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part F:

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“…In order to deal with poor quality images, a selective stereo matching algorithm is developed and applied to the moving regions. First, a disparity map is computed for all moving pixels according to a dissimilarity function entitled Weighted Average Color Difference (WACD) detailed in Fakhfakh et al (2010). An unsupervised classification technique is then applied to the initial set of matching pixels.…”

Section: Overview Of the Avs Systemmentioning

confidence: 99%

“…Indeed, those conventional obstacle detection systems have been used to prevent collisions between trains Intelligent Surveillance System Based on Stereo Vision for Level Crossings Safety Applications and automobiles. In Fakhfakh et al (2010), the conventional technologies applied at LC are discussed and both the advantages and drawbacks of each are highlighted.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Surveillance System Based on Stereo Vision for Level Crossings Safety Applications

Fakhfakh¹,

Khoudour²,

Bruyelle³

et al. 2012

Recent Developments in Video Surveillance

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“…One can cite the single camera based system placed on a high pole in a corner of a level crossing [4]. Otha and Fakhfakh have proposed stereo vision based surveillance systems [5] [6]. In these works, authors choose generally the position and orientation of the cameras by playing experimentally and empirically potential geometrical configurations.…”

Section: Introductionmentioning

confidence: 99%

A descriptive geometry based method for total and common cameras fields of view optimization

2011

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The presented work is conducted in the framework of the ANR-VTT PANsafer project (Towards a safer level crossing). One of the objectives of the project is to develop a video surveillance system that will be able to detect and recognize potential dangerous situation around level crossings. This paper addresses the problem of cameras positioning and orientation in order to view optimally monitored scenes. In general, adjusting cameras position and orientation is achieved experimentally and empirically by considering geometrical different configurations. This step requires a lot of time to adjust approximately the total and common fields of view of the cameras, especially when constrained environments, like level crossing environments, are considered. In order to simplify this task and to get more precise cameras positioning and orientation, we propose in this paper a method that optimizes automatically the total and common cameras fields with respect to the desired scene. Based on descriptive geometry, the method estimates the best cameras position and orientation by optimizing surfaces of 2D domains that are obtained by projecting/intersecting the field of view of each camera on/with horizontal and vertical planes. The proposed method is evaluated and tested to demonstrate its effectiveness.

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A Video-Based Object Detection System for Improving Safety at Level Crossings

Cited by 14 publications

References 19 publications

A review of the technological developments for interlocking at level crossing

A review of the technological developments for interlocking at level crossing

Intelligent Surveillance System Based on Stereo Vision for Level Crossings Safety Applications

A descriptive geometry based method for total and common cameras fields of view optimization

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