Improved Facial-Feature Detection for AVSP via Unsupervised Clustering and Discriminant Analysis
(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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Abstract
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.
| Item Type: | Journal Article |
|---|---|
| RM Number: | 2004001664 |
| Status: | Published |
| Keywords: | audio-visual speech processing, facial-feature detection, unsupervised clustering, discriminant analysis |
| Subjects: | Subjects UNSPECIFIED |
| ID Code: | 10093 |
| Deposited By: | Bozzetto, Adam |
| Deposited On: | 11 October 2007 |
| Alternative Locations: | http://dx.doi.org/10.1155/S1110865703209045 |
| Copyright Owner: | Copyright 2003 (The authors) |
| Additional Information: | The contents of this journal can be freely accessed online via the journal’s web page (see hypertext link). |