Persistent audio modelling for background determination
This paper is concerned with modelling background audio online to detect foreground sounds in complex audio environments for surveillance and smart home applications. We examine and expand upon previous work in the audio and video domains, and propose a new implementation of an audio background mode...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE Computer Society
2005
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| Online Access: | http://hdl.handle.net/20.500.11937/41824 |
| _version_ | 1848756250604470272 |
|---|---|
| author | Moncrieff, Simon West, Geoffrey Venkatesh, Svetha |
| author2 | SuviSoft Oy Ltd |
| author_facet | SuviSoft Oy Ltd Moncrieff, Simon West, Geoffrey Venkatesh, Svetha |
| author_sort | Moncrieff, Simon |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper is concerned with modelling background audio online to detect foreground sounds in complex audio environments for surveillance and smart home applications. We examine and expand upon previous work in the audio and video domains, and propose a new implementation of an audio background modelling algorithm, addressing the complexities of audio data. A number of audio features characterizing different aspects of the audio content were analysed to determine the factors relevant to the determination of the background audio. We test the algorithms on three audio data sets of varying complexity. The new approach was successful in modelling the background audio for the test data. |
| first_indexed | 2025-11-14T09:09:13Z |
| format | Conference Paper |
| id | curtin-20.500.11937-41824 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:09:13Z |
| publishDate | 2005 |
| publisher | IEEE Computer Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-418242017-09-13T15:57:40Z Persistent audio modelling for background determination Moncrieff, Simon West, Geoffrey Venkatesh, Svetha SuviSoft Oy Ltd This paper is concerned with modelling background audio online to detect foreground sounds in complex audio environments for surveillance and smart home applications. We examine and expand upon previous work in the audio and video domains, and propose a new implementation of an audio background modelling algorithm, addressing the complexities of audio data. A number of audio features characterizing different aspects of the audio content were analysed to determine the factors relevant to the determination of the background audio. We test the algorithms on three audio data sets of varying complexity. The new approach was successful in modelling the background audio for the test data. 2005 Conference Paper http://hdl.handle.net/20.500.11937/41824 10.1109/ICME.2005.1521355 IEEE Computer Society fulltext |
| spellingShingle | Moncrieff, Simon West, Geoffrey Venkatesh, Svetha Persistent audio modelling for background determination |
| title | Persistent audio modelling for background determination |
| title_full | Persistent audio modelling for background determination |
| title_fullStr | Persistent audio modelling for background determination |
| title_full_unstemmed | Persistent audio modelling for background determination |
| title_short | Persistent audio modelling for background determination |
| title_sort | persistent audio modelling for background determination |
| url | http://hdl.handle.net/20.500.11937/41824 |