DocumentCode :
2694015
Title :
A real-time approach to the lip-motion extraction in video sequence
Author :
Zhang, Jian-Ming ; Tao, Hong ; Wang, Liang-Min ; Zhan, Yong-Zhao ; Song, Shun-Lin
Author_Institution :
Sch. of Comput., Jiangsu Univ., Zhenjiang, China
Volume :
7
fYear :
2004
fDate :
10-13 Oct. 2004
Firstpage :
6423
Abstract :
A three-stage method to extract the visual pronunciation feature of lip movements is presented in this paper. Firstly, an approach using the "Red Exclusion + Fisher Transformation\´\´ to enhance the chromatic images in video sequences is presented, then an algorithm for segmenting the enhanced gray images with adaptive thresholding is proposed to get the box of the lip regions. Secondly, the authors classify the lip sub-images in the obtained boxes according to the visual-pronunciation features, and two formulae are presented to normalize the dimensions and the gray values of these sub-images, then a method based on SVD is used to extract features from the normalized images. Finally, the matching template based on Mahalanobis distance is applied to recognize lipshapes. The experimental results show that the features extracted by this method have the advantages of the lower dimension, more information and applicable in natural conditions over the available methods.
Keywords :
feature extraction; image segmentation; image sequences; singular value decomposition; Mahalanobis distance; Red Exclusion + Fisher Transformation; adaptive thresholding; gray images segmentation; lip-motion extraction; singular value decomposition; video sequence; visual pronunciation feature; Data mining; Face detection; Feature extraction; Gray-scale; Image segmentation; Linear discriminant analysis; Shape; Singular value decomposition; Speech synthesis; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-8566-7
Type :
conf
DOI :
10.1109/ICSMC.2004.1401410
Filename :
1401410
Link To Document :
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