A mixture model for representing shape variation
A mixture model for representing shape variation
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DOI：
10.1016/s0262-8856(98)00175-9
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发表时间：
1999-06-01
影响因子：
4.7
通讯作者：
Taylor, CJ
中科院分区：
文献类型：
--
作者：
Cootes, TF;Taylor, CJ
一类物体所显示的形状变化可以表示为概率密度函数，使我们能够确定类的合理和不合理的例子。给定一组示例形状的训练集，我们可以将它们对齐到一个共同的坐标框架中，并使用基于核的密度估计技术来表示这种分布。这样的估计是复杂和昂贵的，所以我们使用混合高斯产生一个更简单的近似。我们将展示如何计算分布，以及如何将其用于图像搜索，以在新图像中定位建模对象的示例。(C)1999 Elsevier Science B.V.保留所有权利。
The shape variation displayed by a class of objects can be represented as probability density function, allowing us to determine plausible and implausible examples of the class. Given a training set of example shapes we can align them into a common co-ordinate frame and use kernel-based density estimation techniques to represent this distribution. Such an estimate is complex and expensive, so we generate a simpler approximation using a mixture of gaussians. We show how to calculate the distribution, and how it can be used in image search to locate examples of the modelled object in new images. (C) 1999 Elsevier Science B.V. All rights reserved.