Abstract
Automatic lip tracking is based on robust lip location and segmentation. Here an algorithm which can locate the position of the lips robustly without the constraints of lip highlighting or special lighting conditions is proposed. The proposed method is based on the directional properties of the features of co-occurrence matrices to distinguish between facial parts. The method essentially consists of three parts: a) a face location module b) a facial features location module c) a feature identification module which identifies the lips. The proposed algorithm uses the hue information only in the HSV colour space. The method has been tested on the XM2VTS database, with a high success rate. The use of hue and textural features to do the processing makes the algorithm robust under various lighting conditions.
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References
Auckerthaler, R, Brand, J, Mason J.S., Deravi, F., and Chibelushi, C.C. ‘Lip Signatures for Automatic Person Recognition’ 2nd International Conference on Audio and Video-based Biometric Person Authentication, March 22–23, 1999, Washington, DC, USA, pp. 142–147.
Matthews, I., Bangham, J.A., and Cox, S. ‘Scale Based Features For Audio-Visual Speech Recognition,’ IEE Colloquium on Integrated Audio-Visual Processing for Recognition, Synthesis and Communication, London, Nov. 1996.
Sanchez, M., Matas, J, and Kittler J. ‘Statistically chromaticity model for lip-tracking with B-splines.’ AVBPA’97.
Chindaro S. and Deravi F. ‘Lip Localisation Using Chromaticity Information’ Proc. 1st Conf. In Colour in Graphics and Image Processing’, Saint-Ettienne, France ‘00. pp. 343–347.
Vogt M. ‘Interpreted multi-state lip models for audio-video speech recognition’ In Proc. Of the Audio-Visual Speech Processing, Coignitive and Computational Approaches Workshop, ISSN 1018-4554, Rhodes,Greece 1997.
Delmas P., Coulon P.Y.,and Fristot V., ‘Automatic Snakes for Robust Lip Location’ IEEE Int. Conf. On Acoustics Speech, and Signal Processing, Proceedings, 15–19 March 1999, pp. 3069–3072.
Haralick R.M, Shanmugam K., and Dinstein I. ‘Textural Features For Image Classification’ IEEE Trans. On Syst., Man and Cybernetics, vol. Smc-3,,no. 6, pp. 610–621, 1973.
Paschos G. ‘Chromatic correlation Features for Texture Recognition’ Pattern Recognition Letters Vol. 19, 1998 pp. 643–650.
Dai Y. and Nakano Y. ‘Face-Texture Model Based on SGLD an its Application In Face Detection in a Colour Scene’ Pattern Recognition, Vol. 29, no, pp. 1007–1017, 1996.
The XM2VTS Face Database web site, http://www.ee.surrey.ac.uk/Research/VSSP/xm2vtsdb/ .
Foely, J., VAN Dam, A., Feiner, S., and Hughes, J. ‘Computer Graphics: Principals and Practice’ Addison Wesley, Reading, MA, 1990.
M.J. Jones and J.M. Rehg ‘Statistical Colour Models with Application To Skin Detection’ Cambridge Research Laboratory, Technical Report Series, Compaq, (Dec. 1998).
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© 2001 Springer-Verlag Berlin Heidelberg
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Chindaro, S., Deravi, F. (2001). Directional Properties of Colour Co-occurrence Features for Lip Location and Segmentation. In: Bigun, J., Smeraldi, F. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2001. Lecture Notes in Computer Science, vol 2091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45344-X_13
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DOI: https://doi.org/10.1007/3-540-45344-X_13
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