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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Kim, H.-J., Ryu, T.-W., Lee, J., & Yang, H.-S. (2006). Face Detection Using an Adaptive Skin-Color Filter and FMM Neural Networks (pp. 1171–1175). https://doi.org/10.1007/978-3-540-36668-3_155
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