Audio-video event recognition system for public transport security

Vu, Van-Thinh; Brémond, François; Davini, Gabriele; Thonnat, Monique; Pham, Quoc-Cuong; Allezard, Nicolas; Sayd, Patrick; Rouas, Jean-Luc; Ambellouis, Sébastien; Flancquart, Amaury

doi:10.1049/ic:20060345

Cited by 26 publications

(17 citation statements)

References 16 publications

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“…Video surveillance systems have been around for many years but have limitations such as limited field of view and relatively expensive computation and data storage. An ASR system could be used to complement a video-based recognition system such as in public transports [139], detecting traffic events [140], fall detection [141], machine awareness [142], and in banks [143]. Audio and video recognition systems could also be combined for recognition of complex events in real movies [144].…”

Section: Spectral Features Hmmmentioning

confidence: 99%

An overview of applications and advancements in automatic sound recognition

Sharan

Moir

2016

Neurocomputing

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a b s t r a c tAutomatic sound recognition (ASR) has attracted increased and wide ranging interests in recent years. In this paper, we carry out a review of some important contributions in ASR techniques, mainly over the last one and a half decades. Similar to speech recognition systems, the robustness of an ASR system largely depends on the choice of feature(s) and classifier(s). We take a wider perspective in providing an overview of the features and classifiers used in ASR systems starting from early works in content-based audio classification to more recent developments in applications such as sound event recognition, audio surveillance, and environmental sound recognition. We also review techniques that have been utilized in noise robust sound recognition systems and feature optimization methods. Finally, some of the less commonly known applications of ASR are discussed.

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Section: Spectral Features Hmmmentioning

confidence: 99%

An overview of applications and advancements in automatic sound recognition

Sharan

Moir

2016

Neurocomputing

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“…In (Vu et al, 2006), an event recognition system based on face detection and tracking combined with audio analysis is presented. Zones of interest and static objects are used as context information.…”

Section: Related Workmentioning

confidence: 99%

PASSENGER COUNTING IN PUBLIC RAIL TRANSPORT - Using Head-Shoulder Contour Tracking

Potter¹,

Belet²,

Poppe³

et al. 2012

Proceedings of the International Conference on Computer Vision Theory and Applications

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Abstract:Automated people counting has multiple applications: referring passengers to vehicles with empty seats, gathering statistical information for railway companies to improve their distribution of vehicles, etc. In this paper, a people counting algorithm for public transport vehicles is presented. First, head-shoulder contours are detected by adaboost classification of a combination of a histogram of oriented gradients features and a color histogram. An integral histogram and integral image are used to speed up the extraction of these features.The results of the classification process are clustered and these clusters are tracked by a Kalman filter using a custom error covariance matrix. Finally, the path followed by an observed person is evaluated in order to count passengers entering and exiting the vehicle. Evaluation shows that this approach performs better than previous approaches, especially in scenarios with occlusions.

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“…Surveillance applications have been developed to solve these problems, inspiring significant research in several fields, such as cognitive video and audio [ 1 , 2 ], radio frequency identification (RFID) [ 3 , 4 ], biometric recognition [ 5 ], decision support systems [ 6 , 7 ], distributed architectures [ 8 ] and sensors network [ 9 , 10 ]. Some approaches combine one or more of these technologies in the context of intrusions.…”

Section: Introductionmentioning

confidence: 99%

Consolidation of a WSN and Minimax Method to Rapidly Neutralise Intruders in Strategic Installations

Conesa-Muñoz

Ribeiro

2012

Sensors

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Due to the sensitive international situation caused by still-recent terrorist attacks, there is a common need to protect the safety of large spaces such as government buildings, airports and power stations. To address this problem, developments in several research fields, such as video and cognitive audio, decision support systems, human interface, computer architecture, communications networks and communications security, should be integrated with the goal of achieving advanced security systems capable of checking all of the specified requirements and spanning the gap that presently exists in the current market. This paper describes the implementation of a decision system for crisis management in infrastructural building security. Specifically, it describes the implementation of a decision system in the management of building intrusions. The positions of the unidentified persons are reported with the help of a Wireless Sensor Network (WSN). The goal is to achieve an intelligent system capable of making the best decision in real time in order to quickly neutralise one or more intruders who threaten strategic installations. It is assumed that the intruders’ behaviour is inferred through sequences of sensors’ activations and their fusion. This article presents a general approach to selecting the optimum operation from the available neutralisation strategies based on a Minimax algorithm. The distances among different scenario elements will be used to measure the risk of the scene, so a path planning technique will be integrated in order to attain a good performance. Different actions to be executed over the elements of the scene such as moving a guard, blocking a door or turning on an alarm will be used to neutralise the crisis. This set of actions executed to stop the crisis is known as the neutralisation strategy. Finally, the system has been tested in simulations of real situations, and the results have been evaluated according to the final state of the intruders. In 86.5% of the cases, the system achieved the capture of the intruders, and in 59.25% of the cases, they were intercepted before they reached their objective.

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Audio-video event recognition system for public transport security

Cited by 26 publications

References 16 publications

An overview of applications and advancements in automatic sound recognition

An overview of applications and advancements in automatic sound recognition

PASSENGER COUNTING IN PUBLIC RAIL TRANSPORT - Using Head-Shoulder Contour Tracking

Consolidation of a WSN and Minimax Method to Rapidly Neutralise Intruders in Strategic Installations

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