Abstract
In this paper we present a computer vision architecture to detect and track the face and hands of a human being in real time from a video sequence captured by a webcam. The architecture has a first preprocessing stage, including a color filtering module, a motion filtering module, a color-based segmentation, a processing channels merge module and, finally, a contour search and discrimination module. The aim of the first stage is to discard the image regions which are highly unlikely to correspond with skin. Thus, the second stage of the architecture is a previously trained Fuzzy ARTMAP multiscale neural network module which only processes those image regions selected by the preprocessing stage, which are fully expected to be skin. The neural networks make the last decision about face and hand detection. After that, the architecture tracks the trajectories which face and hands follow.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Yang, M.-H., Kriegman, D.J., Ahuja, N.: Detecting Faces in Images: A Survey. IEEE Trans. Pattern Analysis and Machine Intelligence. 24(1), 34–58 (2002)
Petajan, E., Graf, H.P., Chen, T., Cosatto, E.: Locating Faces and Facial Parts. In: Proc. Int’l Conf. Automatic Face and Gesture Recognition, pp. 41–46 (1995)
Burl, M.C., Leung, T.K., Perona, P.: Face Localisation via Shape Statistics. In: Proc. Int’l Conf. Automatic Face and Gesture Recognition, pp. 154–159 (1995)
Brunelli, R., Poggio, T.: Face recognition: features versus templates. IEEE Trans. Pattern Analysis Machine Inteligence. 15(10), 1042–1052 (1993)
Heisele, B., Ho, P., Wu, J., Poggio, T.: Face recognition: component-based versus global approaches. Computer Vision and Image Understanding 91, 6–21 (2003)
Carpenter, G.A., Grossberg, S., Markuzon, N., Reynolds, J.H., Rosen, D.B.: Fuzzy ARTMAP: A Neural Network Architecture for Supervised Learning of Analog Multidimensional Maps. IEEE Trans. Neural Networks 3(5), 698–713 (1992)
Carpenter, G.A., Grossberg, S.: A massively parallel architecture for a self-organizing neural pattern recognition machine. Computer Vision, Graphics and Image Processing 37, 54–115 (1987)
Martin Hunke, H.: Locating and Tracking of Human Faces with Neural Networks. Master’s thesis. University of Karlsruhe (1994)
Yang, M.-H., Ahuja, N.: Detecting Human Faces in Color Images. Proc. IEEE Int’l Conf. Image Processing. 1, 127–130 (1998)
Hsieh, I.-S., Fan, K.-C., Lin, C.: A Statistic Approach to the Detection of Human Faces in Color Nature Scene. Pattern Recognition 35, 1583–1596 (2002)
Spacek, L.: Dataset Faces96, faces database from (2002), http://cswww.essex.ac.uk/allfaces/faces96.html
Rousseeuw, P.J.: Multivariate estimation with high breakdown point. Institute of Mathematical Statistics Bulletin 12, 234 (1983)
Rousseeuw, P.J., Van Driessen, K.: A Fast Algorithm for the Minimum Covariance Determinant Estimator. Technometrics 41, 212–223 (1999)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley, Reading (1992)
Open Source Computer Vision Library: Reference Manual. Intel Corporation (2001)
PICS: The Psychological Image Collection at Stirling, database from the University of Stirling Psychology Department, http://pics.psych.stir.ac.uk
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
González-Ortega, D., Díaz-Pernas, F.J., Díez-Higuera, J.F., Martínez-Zarzuela, M., Boto-Giralda, D. (2006). Computer Vision Architecture for Real-Time Face and Hand Detection and Tracking. In: Bres, S., Laurini, R. (eds) Visual Information and Information Systems. VISUAL 2005. Lecture Notes in Computer Science, vol 3736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590064_4
Download citation
DOI: https://doi.org/10.1007/11590064_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30488-3
Online ISBN: 978-3-540-32339-6
eBook Packages: Computer ScienceComputer Science (R0)