首页> 外文会议>European Conference on Computer Vision(ECCV 2004) pt.4; 20040511-20040514; Prague; CZ >Groupwise Diffeomorphic Non-rigid Registration for Automatic Model Building
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Groupwise Diffeomorphic Non-rigid Registration for Automatic Model Building

机译:自动建立模型的成组微形非刚性配准

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摘要

We describe a framework for registering a group of images together using a set of non-linear diffeomorphic warps. The result of the groupwise registration is an implicit definition of dense correspondences between all of the images in a set, which can be used to construct statistical models of shape change across the set, avoiding the need for manual annotation of training images. We give examples on two datasets (brains and faces) and show the resulting models of shape and appearance variation. We show results of experiments demonstrating that the groupwise approach gives a more reliable correspondence than pairwise matching alone.
机译:我们描述了使用一组非线性微分变形扭曲将一组图像配准在一起的框架。逐组配准的结果是对集合中所有图像之间的密集对应关系的隐式定义,该定义可用于构建整个集合中形状变化的统计模型,而无需人工注释训练图像。我们在两个数据集(大脑和面部)上给出示例,并显示形状和外观变化的结果模型。我们显示的实验结果表明,逐组匹配的方法比逐对匹配的方法更可靠。

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