(Enter summary)
Abstract: A face detection system is presented. A new classi cation method using foreststructured Bayesian networks is used. The method is used in an aggregated classi er to discriminate face from non-face patterns. The process of generating non-face patterns is integrated with the construction of the aggregated classi er. The face detection system performs well in comparison with other well-known methods. (Update)
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.... of algorithms have been proposed that learn segmentation models by statistical analysis of example boundaries, e.g. 4] 8] 3] 11] [1], 21] The methods either tend to disregard the continuous multi feature character of the learning data, neglect the correlations therein,...
.... such as color values and color distributions, edge characteristics, and motion descriptors; and complex descriptors such as face presence [10] and camera movement [1] Due to the large amount of descriptors, it cannot be assumed that they are independent. For example, one...
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BibTeX entry: (Update)
T.V. Pham, M. Worring, and A.W.M. Smeulders. Face detection by aggregated bayesian network classiers. Technical Report 2001-04, Intelligent Sensory Information Systems Group, University of Amsterdam, February 2001. http://citeseer.ist.psu.edu/pham01face.html More
@article{ pham01face,
author = "T. V. Pham and M. Worring and A. W. M. Smeulders",
title = "Face Detection by Aggregated {Bayesian} Network Classifiers",
journal = "Lecture Notes in Computer Science",
volume = "2123",
pages = "249--262",
year = "2001",
url = "citeseer.ist.psu.edu/pham01face.html" }
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