Processing of acoustical data in a multimodal bank operating room surveillance system

Kotus, Józef; źOpatka, K.; Czyżewski, Andrzej; Bogdanis, Georgis

doi:10.1007/s11042-014-2264-z

Cited by 8 publications

(4 citation statements)

References 13 publications

(14 reference statements)

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“…Speaker counting and sound event counting both can contribute to security systems through audio monitoring [21]. Speech as well as the presence of sound in a quiet environment can be indicative of the presence of people and beneficial in home and business monitoring.…”

Section: Security and Surveillancementioning

confidence: 99%

Multimodal System for Audio Scene Source Counting and Analysis

Nigro

Krishnan²

2022

IEEE/ACM Trans. Audio Speech Lang. Process.

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This thesis explores audio scene analysis (ASA) for determining the number of active sources in an audio scene, a task that is defined as audio source counting. A first of its kind dataset called SARdB is produced with audio and text modalities, and annotations for the number of speakers and the number of sound events present in an audio recording. For speaker counting, an audio-based ResNet-34 and text-based Bidirectional Long Short-Term Memory (BLSTM) network set a baseline prediction accuracy of 46.03% and 89.57% when considering a margin of error of one speaker, while outperforming various state-of-the-art systems in speaker counting. Another audio-based ResNet-34 model demonstrates the optimal result for sound event counting at 50.55% prediction accuracy and 86.59% accuracy with a margin of error of one sound event. The proposed method for source counting is also shown to perform in real-time with an overall processing time of ∼0.4614s.

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Section: Security and Surveillancementioning

confidence: 99%

Multimodal System for Audio Scene Source Counting and Analysis

Nigro

Krishnan²

2022

IEEE/ACM Trans. Audio Speech Lang. Process.

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“…The employed methodology can be easily adapted to detect and to classify other types of events. For example, in related authors' work the events occurring in a bank operating hall were detected [17].…”

Section: Classificationmentioning

confidence: 99%

“…In this paper the authors focus on combining their experience with various algorithms to propose a solution which offers full functionality of: detection, classification and localization the acoustic events in real acoustic conditions. The authors have tested their design in several practical implementations, for example in bank operating room [17]. In the present work we concentrate on preparing the setup for testing our design in various and precisely controlled acoustic conditions.…”

mentioning

confidence: 99%

Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations

Lopatka

Kotus

Czyżewski

2015

Multimed Tools Appl

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Evaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier are introduced. The sound source localization algorithm based on the analysis of multichannel signals from the Acoustic Vector Sensor is presented. The methods are evaluated in an experiment conducted in the anechoic chamber, in which the representative events are played together with noise of differing intensity. The results of detection, classification and localization accuracy with respect to the Signal to Noise Ratio are discussed. The results show that the recognition and localization accuracy are strongly dependent on the acoustic conditions. We also found that the engineered algorithms provide a sufficient robustness in moderately intense noise in order to be applied to practical audio-visual surveillance systems.

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“…Similarly, Khera and Verma (2014) look at an autonomous control system for bank vaults to detect and record suspicious movements. Kotus, Łopatka, Czyżewski and Bogdanis (2016) propose a new control system capable of distinguishing between normal sounds and the ones—like shots and screams—caused by threatening circumstances. By simulating a dangerous situation in a real bank branch, the authors tested their system.…”

Section: Introduction: Literature Review and Main Objectivesmentioning

confidence: 99%

Assessing the risk of robbery in bank branches to reduce impact on personnel

et al. 2021

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According to existing literature, bank robberies can have a considerable impact on the people involved (employees, customers, and police officers), even if the direct economic losses are negligible. Consequently, this article presents a model to assess the risk of bank robbery, with the aim of reducing the impact on the people and prioritizing the investments in security measures. It is based on the MIVES (Spanish acronym for the Integrated Value Model for Sustainability Assessment) method and it was combined with Monte Carlo simulation as a way of taking into account the uncertainty. Correlations were also modeled, for simulation purposes. Indicators for addressing issues related to security features, employees, operational procedures, and physical and social environment were defined. The model was applied to two fictitious but realistic sets of cases. The first simulation provides a quick overview of the risk level of a fictitious bank, before collecting the full set of data from hundreds or thousands of branches. The second simulation analyzes the risk variation of a specific bank branch over time. The model was also used to assess the risk index of 636 real branches belonging to a Spanish bank. All the results are presented and discussed in depth. The model allows the user to identify the weak points of a branch, so that corrective measures can be taken.

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Processing of acoustical data in a multimodal bank operating room surveillance system

Cited by 8 publications

References 13 publications

Multimodal System for Audio Scene Source Counting and Analysis

Multimodal System for Audio Scene Source Counting and Analysis

Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations

Assessing the risk of robbery in bank branches to reduce impact on personnel

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