Automatic Audio and Video Event Recognition in an Intelligent Resource Management System
Event recognition systems have high potential to support crisis management and emergency response. For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automati...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Stein, Daniel [verfasserIn] Krausz, Barbara [verfasserIn] Lo§ffler, Jobst [verfasserIn] Marterer, Robin [verfasserIn] Bardeli, Rolf [verfasserIn] Stadtschnitzer, Michael [verfasserIn] Schwenninger, Jochen [verfasserIn] |
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E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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1 Online-Ressource |
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| Übergeordnetes Werk: |
Enthalten in: International journal of information systems for crisis response and management - Hershey, Pa : IGI Global, 2009, 5(2013), 4, Seite 1-12 |
|---|---|
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volume:5 ; year:2013 ; number:4 ; pages:1-12 |
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10.4018/ijiscram.2013100101 |
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NLEJ251812014 |
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| 520 | |a Event recognition systems have high potential to support crisis management and emergency response. For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automatic audio and video event recognition, by means of detecting abnormalities both in train noise as well as surveillance videos, and by conducting automatic speech recognition on fire fighter communication. All components are integrated in an overall intelligent resource management system. The authors elaborate on the challenges expected from real life data and the solutions that the authors applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users' infrastructures. The system has been continuously running for more than two years, collecting data for research purposes | ||
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10.4018/ijiscram.2013100101 doi (DE-627)NLEJ251812014 (VZGNL)10.4018/ijiscram.2013100101 DE-627 ger DE-627 rakwb eng Stein, Daniel verfasserin aut Automatic Audio and Video Event Recognition in an Intelligent Resource Management System 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Event recognition systems have high potential to support crisis management and emergency response. For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automatic audio and video event recognition, by means of detecting abnormalities both in train noise as well as surveillance videos, and by conducting automatic speech recognition on fire fighter communication. All components are integrated in an overall intelligent resource management system. The authors elaborate on the challenges expected from real life data and the solutions that the authors applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users' infrastructures. The system has been continuously running for more than two years, collecting data for research purposes Abnormal Event Detection Automatic Speech Recognition Event-Driven Service-Oriented Architecture Event Recognition System Terrestrial Trunked Radio (TETRA) Channel Krausz, Barbara verfasserin aut Lo§ffler, Jobst verfasserin aut Marterer, Robin verfasserin aut Bardeli, Rolf verfasserin aut Stadtschnitzer, Michael verfasserin aut Schwenninger, Jochen verfasserin aut Enthalten in International journal of information systems for crisis response and management Hershey, Pa : IGI Global, 2009 5(2013), 4, Seite 1-12 Online-Ressource (DE-627)NLEJ244419167 (DE-600)2703397-1 1937-9420 nnns volume:5 year:2013 number:4 pages:1-12 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiscram.2013100101 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiscram.2013100101&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 5 2013 4 1-12 |
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10.4018/ijiscram.2013100101 doi (DE-627)NLEJ251812014 (VZGNL)10.4018/ijiscram.2013100101 DE-627 ger DE-627 rakwb eng Stein, Daniel verfasserin aut Automatic Audio and Video Event Recognition in an Intelligent Resource Management System 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Event recognition systems have high potential to support crisis management and emergency response. For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automatic audio and video event recognition, by means of detecting abnormalities both in train noise as well as surveillance videos, and by conducting automatic speech recognition on fire fighter communication. All components are integrated in an overall intelligent resource management system. The authors elaborate on the challenges expected from real life data and the solutions that the authors applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users' infrastructures. The system has been continuously running for more than two years, collecting data for research purposes Abnormal Event Detection Automatic Speech Recognition Event-Driven Service-Oriented Architecture Event Recognition System Terrestrial Trunked Radio (TETRA) Channel Krausz, Barbara verfasserin aut Lo§ffler, Jobst verfasserin aut Marterer, Robin verfasserin aut Bardeli, Rolf verfasserin aut Stadtschnitzer, Michael verfasserin aut Schwenninger, Jochen verfasserin aut Enthalten in International journal of information systems for crisis response and management Hershey, Pa : IGI Global, 2009 5(2013), 4, Seite 1-12 Online-Ressource (DE-627)NLEJ244419167 (DE-600)2703397-1 1937-9420 nnns volume:5 year:2013 number:4 pages:1-12 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiscram.2013100101 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiscram.2013100101&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 5 2013 4 1-12 |
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Event recognition systems have high potential to support crisis management and emergency response. For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automatic audio and video event recognition, by means of detecting abnormalities both in train noise as well as surveillance videos, and by conducting automatic speech recognition on fire fighter communication. All components are integrated in an overall intelligent resource management system. The authors elaborate on the challenges expected from real life data and the solutions that the authors applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users' infrastructures. The system has been continuously running for more than two years, collecting data for research purposes |
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Event recognition systems have high potential to support crisis management and emergency response. For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automatic audio and video event recognition, by means of detecting abnormalities both in train noise as well as surveillance videos, and by conducting automatic speech recognition on fire fighter communication. All components are integrated in an overall intelligent resource management system. The authors elaborate on the challenges expected from real life data and the solutions that the authors applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users' infrastructures. The system has been continuously running for more than two years, collecting data for research purposes |
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Event recognition systems have high potential to support crisis management and emergency response. For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automatic audio and video event recognition, by means of detecting abnormalities both in train noise as well as surveillance videos, and by conducting automatic speech recognition on fire fighter communication. All components are integrated in an overall intelligent resource management system. The authors elaborate on the challenges expected from real life data and the solutions that the authors applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users' infrastructures. The system has been continuously running for more than two years, collecting data for research purposes |
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Automatic Audio and Video Event Recognition in an Intelligent Resource Management System |
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiscram.2013100101 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiscram.2013100101&buylink=true |
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true |
| author2 |
Krausz, Barbara Lo§ffler, Jobst Marterer, Robin Bardeli, Rolf Stadtschnitzer, Michael Schwenninger, Jochen |
| author2Str |
Krausz, Barbara Lo§ffler, Jobst Marterer, Robin Bardeli, Rolf Stadtschnitzer, Michael Schwenninger, Jochen |
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NLEJ244419167 |
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| doi_str |
10.4018/ijiscram.2013100101 |
| up_date |
2024-07-06T11:40:28.283Z |
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1803829670873923584 |
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For large-scale scenarios, however, the sheer amount of possible audio and video channels requires adequate processing of the material by automatic means. In this article, the authors focus on automatic audio and video event recognition, by means of detecting abnormalities both in train noise as well as surveillance videos, and by conducting automatic speech recognition on fire fighter communication. All components are integrated in an overall intelligent resource management system. The authors elaborate on the challenges expected from real life data and the solutions that the authors applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users' infrastructures. 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