A real time surveillance system for metropolitan railways

Black, J.; Velastín, Sergio A.; Boghossian, B.

doi:10.1109/avss.2005.1577265

Cited by 18 publications

(10 citation statements)

References 10 publications

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“…Chauhan et al proposed a moving object detection method that combines a GMM-based background difference and optical flow to compensate for the disadvantages of typical motion estimation based methods and background difference-based methods [13]. Additional research on the visual surveillance techniques can be found in [14][15][16][17][18][19][20].…”

Section: Related Workmentioning

confidence: 99%

Hybrid Sensor Network-Based Indoor Surveillance System for Intrusion Detection

Park

Kim

et al. 2018

Symmetry

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This paper presents a novel hybrid sensor-based intrusion detection system for low-power surveillance in an empty, sealed indoor space with or without illumination. The proposed system includes three functional steps: (i) initial detection of an intrusion event using a sound field sensor; (ii) automatic lighting control based on the detected event, and (iii) detection and tracking the intruder using an image sensor. The proposed hybrid sensor-based surveillance system uses a sound field sensor to detect an abnormal event in a very low-light or completely dark environment for 24 h a day to reduce the power consumption. After detecting the intrusion by the sound sensor, a collaborative image sensor takes over an accurate detection and tracking tasks. The proposed hybrid system can be applied to various surveillance environments such as an office room after work, empty automobile, safety room in a bank, and armory room. This paper deals with fusion of computer-aided pattern recognition and physics-based sound field analysis that reflects the symmetric aspect of computer vision and physical analysis

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Section: Related Workmentioning

confidence: 99%

Hybrid Sensor Network-Based Indoor Surveillance System for Intrusion Detection

Park

Kim

et al. 2018

Symmetry

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“…[5,6,8]. To detect abrupt and dangerous situations, object tracking has been implemented using a combined method of background subtraction, edge detection and motion detection [9][10][11][12][13][14]. An infrared camera was found to be useful to locate passengers [10].…”

Section: Introductionmentioning

confidence: 99%

“…These systems are focused on measuring the level of crowding on the passenger platforms of train services. If overcrowding is detected, the system will notify the station operators to take appropriate actions to prevent dangerous situations such as people falling off or being pushed onto the tracks [9][10][11][12][13][14]. Background subtraction is commonly used to locate passengers and thereby to estimate the crowd density [1][2][3][4][5]7] Edge information may be used to measure the regions occupied by passengers [1,4].…”

Section: Introductionmentioning

confidence: 99%

3D Vision-based Security Monitoring for Railroad Stations

Park

Lee

2010

Journal of the Optical Society of Korea

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Increasing demands on the safety of public train services have led to the development of various types of security monitoring systems. Most of the surveillance systems are focused on the estimation of crowd level in the platform, thereby yielding too many false alarms. In this paper, we present a novel security monitoring system to detect critically dangerous situations such as when a passenger falls from the station platform, or when a passenger walks on the rail tracks. The method is composed of two stages of detecting dangerous situations. Objects falling over to the dangerous zone are detected by motion tracking. 3D depth information retrieved by the stereo vision is used to confirm fallen events. Experimental results show that virtually no error of either false positive or false negative is found while providing highly reliable detection performance. Since stereo matching is performed on a local image only when potentially dangerous situations are found; real-time operation is feasible without using dedicated hardware.

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“…Four final candidates have successfully submitted their solutions to the specific event detection tasks described in Section 2 and have accepted to follow the performance evaluation procedure described in Section 4. The four proposals are described in detail in [1], [2], [3] and [4].…”

Section: Proposals Submitted To Credsmentioning

confidence: 99%

“…In [2], a block based motion estimation approach is used in a statistical framework to robustly generate background estimation. Foreground segmentation benefits from the robustness of the background and enables the approach to detect several events of interest.…”

Section: Proposals Submitted To Credsmentioning

confidence: 99%

Performance evaluation of event detection solutions: the creds experience

Ziliani¹,

Velastín²,

Porikli³

et al.

Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2005.

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In video surveillance projects, automatic and real-time event detection solutions are required to guarantee an efficient and cost-effective use of the infrastructure. Many solutions have been proposed to automatically detect a variety of events of interest. However, not all solutions and technologies may satisfy all the requirements of the surveillance scenario. For this reason, performance evaluation of existing event detection solutions becomes an important step in the deployment of video surveillance projects. In this paper, we propose a practical approach that aims at minimizing the ground truth generation problem and the expertise required to evaluate and compare the results by introducing specific requirements of specific event detection scenarios. This approach is believed to be applicable for an initial evaluation of candidate solutions to a specific surveillance scenario before more exhaustive tests in an integrated environment. The purposed method is under evaluation in the framework of the Challeng of Real-time Event Detection Solutions (CREDS). IEEE Conference on Advanced Video and Siganl Based SurveillanceThis work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved.

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A real time surveillance system for metropolitan railways

Cited by 18 publications

References 10 publications

Hybrid Sensor Network-Based Indoor Surveillance System for Intrusion Detection

Hybrid Sensor Network-Based Indoor Surveillance System for Intrusion Detection

3D Vision-based Security Monitoring for Railroad Stations

Performance evaluation of event detection solutions: the creds experience

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