Persistent audio modelling for background determination Moncrieff, Simon, Venkatesh, Svetha and West, Geoff 2005, Persistent audio modelling for background determination, in ICME 2005 : Proceedings of the IEEE International Conference on Multimedia and Expo 2005, IEEE, Piscataway, N. J., pp. 41-44. Attached Files Name Description MIMEType Size Downloads venkatesh-persistentaudio-2005.pdf Published version application/pdf 175.49KB 43 Title Persistent audio modelling for background determination Author(s) Moncrieff, Simon Venkatesh, Svetha orcid.org/0000-0001-8675-6631 West, Geoff Conference name IEEE International Conference on Multimedia and Expo (2005 : Amsterdam, The Netherlands) Conference location Amsterdam, The Netherlands Conference dates 6-8 Jul. 2005 Title of proceedings ICME 2005 : Proceedings of the IEEE International Conference on Multimedia and Expo 2005 Editor(s) [Unknown] Publication date 2005 Conference series IEEE International Conference on Multimedia and Expo Start page 41 End page 44 Total pages 4 Publisher IEEE Place of publication Piscataway, N. J. Summary 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 characterising 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. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. ISBN 0780393325 9780780393325 Language eng Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2005, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30044629 Document type: Conference Paper Collections: School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Fri, 20 Apr 2012, 11:36:21 EST Fri, 27 Apr 2012, 12:26:57 EST Fri, 27 Apr 2012, 12:28:01 EST Wed, 02 May 2012, 09:16:00 EST Thu, 03 May 2012, 13:24:54 EST Tue, 06 Sep 2016, 18:47:01 EST Sat, 17 Jun 2017, 03:10:27 EST Sat, 21 Oct 2017, 02:02:34 EST Tue, 05 Dec 2017, 12:31:38 EST Fri, 07 Sep 2018, 15:53:30 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 6 times in Scopus Search Google Scholar Access Statistics: 341 Abstract Views, 43 File Downloads  -  Detailed Statistics Created: Fri, 20 Apr 2012, 11:36:21 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.