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.
Original language | English |
---|---|
Title of host publication | PROCEEDINGS OF SPIE |
Subtitle of host publication | International Conference on Images, Signals, and Computing (ICISC 2023) |
Place of Publication | P.O. Box 10, Bellingham, Washington 98227-0010 USA |
Pages | 127830E-1 - 127830E-7 |
Number of pages | 7 |
Volume | 12783 |
ISBN (Electronic) | 9781510668171 |
Publication status | Published - 24 Aug 2023 |
Event | The 2023 International Conference on Images, Signals, and Computing - Chengdu, China Duration: 27 May 2023 → 29 May 2023 |
Conference
Conference | The 2023 International Conference on Images, Signals, and Computing |
---|---|
Abbreviated title | ICISC |
Country/Territory | China |
Period | 27/05/23 → 29/05/23 |
Research Field
- Former Research Field - New Sensor Technologies
Keywords
- sensor fusion
- acoustics
- security