Exploiting CCTV camera system for advanced passenger services on-board trains

Saponara, Sergio; Pilato, Luca; Fanucci, Luca

doi:10.1109/isc2.2016.7580748

Cited by 14 publications

(21 citation statements)

References 9 publications

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“…The algorithm used for the smoke recognition follows the video processing flow showed in Fig. 5, similarly to what we discussed in [2]. The first step in the algorithm is the video decoding.…”

Section: Smoke and Fire Real-time Prevention Algorithmmentioning

confidence: 99%

“…[width] · [height] · [fps] · [motion rank] · 0.07 = [bitrate] (2) Under the above assumptions from Eq. (2) the H.264 coded bit-rate will be from 400 kbps to 800 kbps, depending on the motion characteristics of the scene.…”

Section: Fire Prevention Implementationmentioning

confidence: 99%

“…For example the work in [19], considered just fire alarm generation in rolling stocks, while using video sensors multiple sensors can be implemented. Instead, using as in [2] only 1 camera the achieved rate of missed detections or false alarms in not acceptable for a fully autonomous system, since the accuracy is 75%, and the intervention of the staff crew is required. By using multiple cameras covering the same zone, as proposed in this paper, the false alarm rate and missed detection are improved, and can go above 90% This puts the basis for an autonomous system.…”

Section: State Of Art Comparisonmentioning

confidence: 99%

“…Multiple services Fusion of multiple views [19] No, only fire alarm No [2] Yes, fire alarms, people counting, driver drowsiness detection No This work Yes…”

Section: Workmentioning

confidence: 99%

“…On-board new public transport vehicles, such as bus, coaches and trains, usually a network of video cameras is installed to provide surveillance services [1][2][3]. Depending in the size of a wagon (e.g.…”

Section: Introduction On Smart Cameras On-board Public Transport Vehimentioning

confidence: 99%

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Real-time image and video processing for advanced services on-board vehicles for passenger transport

Saponara

2018

Real-Time Image and Video Processing 2018

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The paper exploits the video camera available on-board vehicles for public transport, such as trains, coaches, ferryboats, and so on, to implement advanced services for the passengers. The idea is implementing not only surveillance systems, but also passenger services such as: people counting, smoke and/or fire alarm, automatic climate control, e-ticketing. For each wagon, an embedded acquisition and processing unit is used, which is composed by a video multiplexer, and by an image/video signal processor that implements in real-time algorithms for advanced services such as: smoke detection, to give an early alarm in case of a fire, or people detection for people counting, or fatigue detection for the driver. The alarm is then transmitted to the train information system, to be displayed for passengers or the crew staff.

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Section: Smoke and Fire Real-time Prevention Algorithmmentioning

confidence: 99%

Section: Fire Prevention Implementationmentioning

confidence: 99%

Section: State Of Art Comparisonmentioning

confidence: 99%

“…Multiple services Fusion of multiple views [19] No, only fire alarm No [2] Yes, fire alarms, people counting, driver drowsiness detection No This work Yes…”

Section: Workmentioning

confidence: 99%

Section: Introduction On Smart Cameras On-board Public Transport Vehimentioning

confidence: 99%

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