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

An automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect...

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Bibliographic Details
Published in:Multimedia tools and applications 2016-09, Vol.75 (17), p.10787-10805
Main Authors: Kotus, J., Łopatka, K., Czyżewski, A., Bogdanis, G.
Format: Article
Language:English
Subjects:
Acoustics
Algorithms
Analysis
Banks
Classification
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Localization
Mathematical analysis
Monitoring systems
Multimedia Information Systems
Position (location)
Robbery
Sensors
Signal processing
Sound
Special Purpose and Application-Based Systems
Studies
Support vector machines
Surveillance
Surveillance systems
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Summary:An automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of acoustic events. The methods for calculating the direction of coming sound employing an acoustic vector sensor are presented. The localization is achieved by calculating the DOA (Direction of Arrival) histogram. The evaluation of the system based on experiments conducted in a real bank operating room is presented. The results of sound event detection, classification and localization are provided and discussed. The practical usability of the engineered methods is underlined by presenting the results of analyzing a staged robbery situation.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-014-2264-z