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.
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.
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|Item Type:||Journal Article|
|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|
|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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