Spatial clustering of pixels in the mouth area of face images

M. Sadeghi, J. Kittler, K. Messer
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引用次数: 7

Abstract

We propose a method of image segmentation using a Gaussian mixture model of the colour image histogram. The model construction is based on the model validation philosophy of architecture selection (Kittler et al., 2001). In contrast with the k-means clustering approach, the number of segments in the proposed scheme is determined completely automatically. We show that the modelling method can be strengthened by incorporating spatial contextual information. The proposed approach speeds up the modelling process by a factor of three. The advocated methodology is successfully applied to the problem of lip pixel segmentation in face images.
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人脸图像嘴巴区域像素的空间聚类
提出了一种利用彩色图像直方图的高斯混合模型进行图像分割的方法。模型构建基于架构选择的模型验证哲学(Kittler et al., 2001)。与k-means聚类方法相比,该方案中的片段数量完全自动确定。我们表明,可以通过纳入空间上下文信息来加强建模方法。提出的方法将建模过程加快了三倍。该方法已成功应用于人脸图像的唇像素分割问题。
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