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Title: Study of video assisted BSS for convolutive mixtures
Authors: Aubrey, Andrew
Hicks, Yulia
Sanei, Saeid
Chambers, Jonathon
Keywords: Active appearance models
Audio-visual processing
Blind source separation
Feature extraction
Issue Date: 2006
Publisher: © IEEE
Citation: AUBREY, A. ... et al., 2006. Study of video assisted BSS for convolutive mixtures. IN: 2006 12th Digital Signal Processing Workshop and 4th Signal Processing Education Workshop, Jackson Lake Lodge, Grand Teton National Park, Wyoming, USA, 24-27 September, pp. 273-277.
Abstract: In this paper we present an overview of recent research in the area of audio-visual blind source separation (BSS), together with new results of our work that highlight the advantage of including visual information into a BSS algorithm. In our work the visual information is combined with audio information to form joint audio-visual feature vectors. The audio-visual coherence is then modelled using statistical models. The outputs of these models are used within a frequency domain BSS algorithm to control the step size. Experimental results verify the improvement of the audio-visual method compared to audio only BSS. We also discuss visual feature extraction techniques, along with several recently published methods for audio-visual BSS, and conclude with suggestions for future research.
Description: This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/DSPWS.2006.265389
URI: https://dspace.lboro.ac.uk/2134/5610
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

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