Abstract
In this paper, we propose multi-class classifier and knowledge based face detection. Eye region and face location is used illuminant based Bayesian detector. We propose the efficient face and eye detection system using varying illuminant context modeling and multi–classifier. The face detection system architecture use cascade method by illuminant face model. Also, we detect eye region after face detection. Proposed eye detection frame is multiple illuminant Bayesian classifiers. Because face images have varying illuminant and this is vary difficult problem in face detection. Therefore, we made in context model using face illuminant. The multiple classifiers consist of face illuminant information. Multiple Bayesian classifiers are employed for selection of face and eye detection windows on illuminant face group. Finally, face and eye regions of the detected candidates are selected by context awareness.
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
van Leeuwen, J.: Computer Science Today. LNCS, vol. 1000. Springer, Heidelberg (1995)
Haro, M., Flickner, F.A.: Detecting and tracking eyes by using their physiological properties, dynamics, and appearance. In: Proc. Of IEEE Conf. on CVPR (2000)
Baskan, S., Bulut, M.M., Atalay, V.: Projection based method for segmentation of human face and its evaluation. Pattern Recognition Letters 23, 1623–1629 (2002)
Lucey, S., Sridharan, S., Chandran, V.: Improved facial feature detection for AVSP via unsupervised clustering and dicriminant analysis. EURASIP Journal on Applied Signal Processing 3, 264–275 (2003)
Liu, C.: A Bayesian Discriminating Features Method for Face Detection. IEEE Trans. Pattern Analysis and Machine Intelligence 25, 725–740 (2003)
Pham, T.V., et al.: Face detection by aggregated Bayesian network classifiers. Pattern Recognition Letters 23, 451–461 (2002)
Wren, C., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: Real-Time Tracking of the Human Body. Technical Report 353, Media Laboratory, Massachusetts Institute of Technology (1995)
Phillips, P.: The FERET database and evoluation procedure for face recognition algorithms. Image and Vision Computing 16(5), 295–306 (1999)
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
Nam, M.Y., Koh, E.J., Rhee, P.K. (2006). An Efficient Face and Eye Detector Modeling in External Environment. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_88
Download citation
DOI: https://doi.org/10.1007/11785231_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35748-3
Online ISBN: 978-3-540-35750-6
eBook Packages: Computer ScienceComputer Science (R0)