Abstract
In this paper we present a skin color approach for fast and accurate face detection which combines skin color learning and image segmentation. This approach starts from a coarse segmentation which provides regions of homogeneous statistical color distribution. Some regions represent parts of human skin and are selected by minimizing an error between the color distribution of each region and the output of a compression decompression neural network, which learns skin color distribution for several populations of different ethnicity. This ANN is used to find a collection of skin regions which are used to estimate the new parameters of the Gaussian models using a 2-means fuzzy clustering in order to adapt these parameters to the context of the input image. A Bayesian framework is used to perform a finer classification and makes the skin and face detection process invariant to scale and lighting conditions. Finally, a face shape based model is used to validate or not the face hypothesis on each skin region.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
H. Rowley, S. Baluja and T. Kanade: Neural network-based face detection. In IEEE Trans on PAMI. Vol. 20, Num. 1. (1998) 23–38.
E. Osuna, R. Freund and F. Girosi: Training support vector machines: an application to face detection. In IEEE CVPR. (1997) 130–136.
T. Leung, M.C. Burl and P Perona: Finding faces in cluttered scenes using random labelled graph matching. In ICCV. (1995).
J. Cai and A. Goshtasby: Detecting humans faces in color images. Image and Vision Computing. Vol. 18, Num. 1. (2000) 63–75.
F. Fleuret and D. Geman: Coarse-to-fine visual selection. In IJCV. Vol. 41, Num. 2. (2001).
P. Viola and M. Jones: Robust real-time object detection. In Second International Workshop On Statistical and Computational Theories of Vision-Modeling, Learning, Computing and Sampling. (2001).
A. Winter and C. Nastar: Differential feature distribution maps for image segmentation and region queries in image databases. CBAIVL workshop at CVPR. (1999).
C.M. Bishop: Neural networks for pattern recognition. CLARENDON PRESS OXFORD. (1995).
Rajesh N. Dave: Characterization and detection of noise in clustering. Pattern Recognition. Vol. 12, Num. 11. (1995) 545–561.
S. Gilles: Robust description and matching of images. Oxford University. (1998).
H. Sahbi, D. Geman and N. Boujemaa: Face detection using coarse-to-fine support vector classifiers. Submitted to the IEEE, ICIP. (2002).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sahbi, H., Boujemaa, N. (2002). Coarse to Fine Face Detection Based on Skin Color Adaption. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds) Biometric Authentication. BioAW 2002. Lecture Notes in Computer Science, vol 2359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47917-1_12
Download citation
DOI: https://doi.org/10.1007/3-540-47917-1_12
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43723-9
Online ISBN: 978-3-540-47917-8
eBook Packages: Springer Book Archive