Comparison of Depth-based Features for Lipreading

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F14%3A%230003111" target="_blank" >RIV/46747885:24220/14:#0003111 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Comparison of Depth-based Features for Lipreading
Original language description
We examine the effect of depth information captured by Microsoft Kinect on the task of visual speech recognition. We propose depth-based active appearance model (AAM) features and show improved results over discrete cosine transform (DCT). The visual anddepth features are evaluated on a database of 54 speakers each uttering 50 isolated words. In order to exploit the speech dynamics, the features are enhanced by a simplified one-stage variant of hierarchical linear discriminant analysis (Hi-LDA). In theexperiments, we consider feature fusion via combined video-depth active appearance model as a form of early integration, and compare it to traditional multi-stream hidden Markov Model as a form of decision fusion. We also perform experiments on audio-visual recognition in noisy environments and show improved results of incorporating depth information over both traditional audio-video fusion and utilization of speech enhancement algorithms.
Czech name
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Czech description
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Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proc. of Telecommunications and Signal Processing (TSP) conference
ISBN
978-80-214-4983-1
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
648-651
Publisher name
IEEE
Place of publication
Berlín, Německo
Event location
Berlín, Německo
Event date
Jan 1, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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