Improved Facial-Feature Detection for AVSP via Unsupervised Clustering and Discriminant Analysis

Lucey, Simon, Sridharan, Sridha, & Chandran, Vinod (2003) Improved Facial-Feature Detection for AVSP via Unsupervised Clustering and Discriminant Analysis. EURASIP Journal on Applied Signal Processing, 2003(3), pp. 264-275.


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An integral part of any audio-visual speech processing (AVSP) system is the front-end visual system that detects facial-features (e.g., eyes and mouth) pertinent to the task of visual speech processing. The ability of this front-end system to not only locate, but also give a confidence measure that the facial-feature is present in the image, directly affects the ability of any subsequent post-processing task such as speech or speaker recognition. With these issues in mind, this paper presents a framework for a facial-feature detection system suitable for use in an AVSP system, but whose basic framework is useful for any application requiring frontal facial-feature detection. A novel approach for facial-feature detection is presented, based on an appearance paradigm. This approach, based on intraclass unsupervised clustering and discriminant analysis, displays improved detection performance over conventional techniques.

Impact and interest:

10 citations in Scopus
9 citations in Web of Science®
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177 since deposited on 11 Oct 2007
3 in the past twelve months

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ID Code: 10093
Item Type: Journal Article
Refereed: Yes
Additional Information: The contents of this journal can be freely accessed online via the journal’s web page (see hypertext link).
Keywords: audio, visual speech processing, facial, feature detection, unsupervised clustering, discriminant analysis
DOI: 10.1155/S1110865703209045
ISSN: 1110-8657
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2003 (The authors)
Deposited On: 11 Oct 2007 00:00
Last Modified: 29 Feb 2012 13:03

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