Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Improved Facial-Feature Detection for AVSP via Unsupervised Clustering and Discriminant Analysis | EURASIP Journal on Applied Signal Processing 2003 3 264-275 2003 Hindawi Publishing Corporation Improved Facial-Feature Detection for AVSP via Unsupervised Clustering and Discriminant Analysis Simon Lucey Speech Research Laboratory RCSAVT School of Electrical and Electronic Systems Engineering Queensland University of Technology GPO Box 2434 Brisbane QLD 4001 Australia Email slucey@ Sridha Sridharan Speech Research Laboratory RCSAVT School of Electrical and Electronic Systems Engineering Queensland University of Technology GPO Box 2434 Brisbane QLD 4001 Australia Email Vinod Chandran Speech Research Laboratory RCSAVT School of Electrical and Electronic Systems Engineering Queensland University of Technology GPO Box 2434 Brisbane QLD 4001 Australia Email Received 22 February 2001 and in revised form 21 June 2002 An integral part of any audio-visual speech processing AVSP system is the front-end visual system that detects facial features . 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 postprocessing task such as speech or speaker recognition. With these issues in mind this paper presents a framework for a facialfeature 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. Keywords and phrases audio-visual speech processing facial-feature detection unsupervised clustering discriminant analysis. 1. INTRODUCTION The visual speech modality plays an important role in the .
