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Abstract
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.
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Authors (4)
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Georgis Bogdanis
- Microsystem Sopot, Poland
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Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/s11042-014-2264-z
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
MULTIMEDIA TOOLS AND APPLICATIONS
no. 75,
edition 17,
pages 1 - 19,
ISSN: 1380-7501 - Language:
- English
- Publication year:
- 2016
- Bibliographic description:
- Kotus J., Łopatka K., Czyżewski A., Bogdanis G.: Processing of acoustical data in a multimodal bank operating room surveillance system // MULTIMEDIA TOOLS AND APPLICATIONS. -Vol. 75, iss. 17 (2016), s.1-19
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/s11042-014-2264-z
- Verified by:
- Gdańsk University of Technology
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