Multi-Sensor Fusion for the Security Surveillance of Public Areas

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Abstract

Increasing security awareness in the public sector are leading to a more and more widespread use of surveillance applications. Although the available technologies like video processing are already well advanced, they still suffer from high false alarm rates when used under realistic conditions. We present a method for sensor fusion based on probability density maps and a rule engine. The system was tested in a public area using the combination of audio localization, audio classification and video detection using 79 simulated scenarios and 44 hours of sample data recorded over a period of several weeks. The false positive rate decreased by 60% and the event localization rate increased by 25% with the fusion approach compared to the detection performance of individual techniques.
OriginalspracheEnglisch
TitelPROCEEDINGS OF SPIE
UntertitelInternational Conference on Images, Signals, and Computing (ICISC 2023)
ErscheinungsortP.O. Box 10, Bellingham, Washington 98227-0010 USA
Seiten127830E-1 - 127830E-7
Seitenumfang7
Band12783
ISBN (elektronisch)9781510668171
PublikationsstatusVeröffentlicht - 24 Aug. 2023
VeranstaltungThe 2023 International Conference on Images, Signals, and Computing - Chengdu, China
Dauer: 27 Mai 202329 Mai 2023

Konferenz

KonferenzThe 2023 International Conference on Images, Signals, and Computing
KurztitelICISC
Land/GebietChina
Zeitraum27/05/2329/05/23

Research Field

  • Ehemaliges Research Field - New Sensor Technologies

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