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From Coarse to Fine Skin and Face Detection

机译:从粗糙到细皮肤和面部检测

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A method for fine skin and face detection is described that starts from a coarse color segmentation. Some regions represent partes of human skin and are selected by minimizing an aeror between the color distribution of each region and the output of a compression decompression neural network, which learns skin color distribution for several populations of different ethnicity. This ANN is used to fine a collection of skin regions, which is used in a second learning step to provide parameters for a Gaussian mixture model. A finer classification is perormed using a Bayesian framework and makes the skin and face detection invariant to scale and lighting conditions. Finally, a face shape based model is used to decide whether a skin region is a face or not.
机译:描述了一种从粗色分割开始的细皮肤和面部检测的方法。一些地区代表人体皮肤的一部分,并通过最小化每个区域的颜色分布与压缩解压缩神经网络的输出之间的空气,这就学会了几种不同种族的少数种群的肤色分布。该ANN用于精细地集合皮肤区域,其用于第二学习步骤以提供高斯混合模型的参数。使用贝叶斯框架来围绕更好的分类,并使皮肤和面部检测不变,以规模和照明条件。最后,使用基于面形的模型来决定皮肤区域是否是面部。

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