NDLI: A method of visual speech feature area localization

Content Provider	IEEE Xplore Digital Library
Author	Shan Meng Youwei Zhang
Copyright Year	2003
Description	Author affiliation: Inst. of Inf. Sci., Wuyi Univ., Guangdong, China (Shan Meng)
Abstract	In audio-visual bimodal man-machine interaction, extracting Region Of Interest (ROI) that carries visual speech features is a very crucial step. In this paper, our work about ROI localization is described in detail. First, we propose a simplified human skin color model to segment input images and estimate the location of human face. When we locate ROI in the human face area, the traditional linear methods' performance cannot satisfy system's need, especially for unseen subjects. Then we propose a new localization method that is a combination of Support Vector Machine (SVM) and Distance of Likelihood in Feature Space (DLFS) derived from Kernel Principal Component Analysis (KPCA). Results show that the new method outperformed traditional linear ones. All experiments are based on Chinese Audio-Visual Speech Database2 (CAVSD).
Sponsorship	IEEE Circuits and Syst. Soc. (CASS) IEEE R10 CASS IEEE Beijing Section Chinese Neural Networks Council Circuits and Information Processing Committee, CASS-CIE Southeast Univ., China
Starting Page	1173
Ending Page	1176
File Size	247733
Page Count	4
File Format	PDF
ISBN	0780377028
DOI	10.1109/ICNNSP.2003.1281078
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-12-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Image segmentation Humans Speech Skin Spatial databases Man machine systems Face Kernel Principal component analysis
Content Type	Text
Resource Type	Article

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