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Experiments in curvature-based segmentation of range data

机译:基于曲率的范围数据分割实验

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This paper focuses on the experimental evaluation of a range image segmentation system which partitions range data into homogeneous surface patches using estimates of the sign of the mean and Gaussian curvatures. The authors report the results of an extensive testing program aimed at investigating the behavior of important experimental parameters such as the probability of correct classification and the accuracy of curvature estimates, measured over variations of significant segmentation variables. Evaluation methods in computer vision are often unstructured and subjective: this paper contributes a useful example of extensive experimental assessment of surface-based range segmentation.
机译:本文着重于范围图像分割系统的实验评估,该系统使用均值和高斯曲率的符号估计将范围数据划分为均匀的表面斑块。作者报告了一项广泛的测试程序的结果,该程序旨在调查重要实验参数的行为,例如正确分类的概率和曲率估计的准确性,这些变化是通过对重要细分变量的变化进行测量而得出的。计算机视觉中的评估方法通常是结构化和主观的:本文为基于表面的范围分割的广泛实验评估提供了有用的示例。

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