Abstract
The detection of facial features is a necessary step for a wide range of applications e.g. person verification, lipreading and model-based face coding. Due to changes in illumination, visual angle and facial expressions, the variability of facial features in their appearance is high. A robust approach to facial feature detection has to handle these variations. In this framework, we present an approach for the extraction of eyebrows, eyes, nostrils, mouth and chin. Our approach for facial feature extraction is based on the observation that facial features differ from the rest of the face because of their low brightness. Thus, we detect facial feature candidates by evaluating the topographic greylevel relief of the face region. Based on vertical symmetry, distances between facial features and the assessment of each facial feature, we choose the best face constellation. Incomplete face constellations are considered as well. Once facial features are detected in an image sequence, they can be tracked over time. We perform facial feature tracking by block matching. The best-match position is refined by minima analysis. The success of our approach was tested on 38 different image sequences containing faces.
This work was partially supported by the European ACTS-M2VTS project.
Preview
Unable to display preview. Download preview PDF.
References
M. Bichsel, editor. International Workshop on Automatic Face and Gesture Recognition, Zurich, Switzerland, June 26–28 1995. IEEE Computer Society, Swiss Informaticians Society et al., MultiMedia Laboratory, Department of Computer Science, University of Zurich.
M.C. Burl, T.K. Leung, and P. Perona. Face localization via shape statistics. In International Workshop on Automatic Face and Gesture Recognition, pages 154–159, Zurich, Switzerland, June 26–28 1995.
R. Chellappa, C.L. Wilson, and S. Sirohey. Human and machine recognition of faces: A survey. Proceedings of the IEEE, 83(5):705–740, May 1995.
A. Eleftheriadis and A. Jacquin. Automatic face location, detection and tracking for model-assisted coding of video teleconferencing sequences at low bit-rates. Signal Processing: Image Communication, 7(3):231–248, Jul 1995.
G. Galicia and A. Zakhor. Depth recovery of human facial features from video sequences. In IEEE International Conference on Image Processing, pages 603–606, Washington D.C., USA, October 23–26 1995. IEEE Computer Society Press, Los Alamitos, California.
H.P. Graf, T. Chen, E. Petajan, and E. Cosatto. Locating faces and facial parts. In International Workshop on Automatic Face and Gesture Recognition, pages 41–46, Zurich, Switzerland, June 26–28 1995.
B. S. Manjunath, R. Chellappa, C. Shekhar, and C. von der Malsburg. A robust method for detecting image features with application to face recognition and motion correspondence. In 11th IAPR International Conference on Pattern Recognition, pages 208–212, The Hague, The Netherlands, August 30–September 3 1992. IEEE Computer Society Press.
K. Sobottka and I. Pitas. Extraction of facial regions and features using color and shape information. In Int. Conf. on Pattern Recognition (ICIP), Vienna, Austria, August 1996.
K. Sobottka and I. Pitas. Face localization and facial feature extraction based on shape and color information. In Int. Conf. on Image Processing (ICPR), Lausanne, Switzerland, September 1996.
K. Sobottka and I. Pitas. Looking for faces and facial features in color images. Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications, Russian Academy of Sciences, 1996.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sobottka, K., Pitas, I. (1997). A fully automatic approach to facial feature detection and tracking. In: Bigün, J., Chollet, G., Borgefors, G. (eds) Audio- and Video-based Biometric Person Authentication. AVBPA 1997. Lecture Notes in Computer Science, vol 1206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015982
Download citation
DOI: https://doi.org/10.1007/BFb0015982
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-62660-2
Online ISBN: 978-3-540-68425-1
eBook Packages: Springer Book Archive