Abstract
In this paper we propose a novel method for the detection of events of interest through audio analysis. The system that we propose is based on the representation of the audio streams through a Gammatone image, which describes the time-frequency distribution of the energy of the signal; this representation is inspired by the functioning of the human auditory system. A pool of AdaBoost cascade classifiers, one for each class of events of interest, is involved in the event detection stage. The performance of the proposed system has been evaluated on a large data set of audio events for surveillance applications and the achieved results, compared with two state of the art approaches, confirm its effectiveness.
Original language | English |
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Title of host publication | 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014 |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 50-55 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-4799-4871-0 |
ISBN (Print) | 978-1-4799-4870-3 |
DOIs | |
Publication status | Published - 8 Oct 2014 |
Externally published | Yes |
Event | 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014 - Seoul, Korea, Republic of Duration: 26 Aug 2014 → 29 Aug 2014 Conference number: 11 |
Conference
Conference | 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014 |
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Abbreviated title | AVSS |
Country/Territory | Korea, Republic of |
City | Seoul |
Period | 26/08/14 → 29/08/14 |