Study of Video Assisted BSS for Convolutive Mixtures.pdf (244.48 kB)
Study of video assisted BSS for convolutive mixtures
conference contribution
posted on 2009-12-08, 09:58 authored by Andrew Aubrey, Yulia Hicks, Saeid Sanei, Jonathon ChambersIn 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.
History
School
- Mechanical, Electrical and Manufacturing Engineering
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.Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2006Notes
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.Language
- en