Face detection using an adaptive skin-color filter and FMM neural networks

In this paper, we present a real-time face detection method based on hybrid neural networks. We propose a modified version of fuzzy min-max (FMM) neural network for feature analysis and face classification. A relevance factor between features and pattern classes is defined to analyze the saliency of features. The measure can be utilized for the feature selection to construct an adaptive skin-color filter. The feature extraction module employs a convolutional neural network (CNN) with a Gabor transform layer to extract successively larger features in a hierarchical set of layers. In this paper we first describe the behavior of the proposed FMM model, and then introduce the feature analysis technique for skin-color filter and pattern classifier.
Publisher
SPRINGER-VERLAG BERLIN
Issue Date
2006
Language
ENG
Keywords

CLASSIFICATION

Citation

PRICAI 2006: TRENDS IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS BOOK SERIES: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, v.4099, pp.1171 - 1175

ISSN
0302-9743
URI
http://hdl.handle.net/10203/332
Appears in Collection
CS-Journal Papers(저널논문)
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