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New measure for objective evaluation of mesh segmentation algorithms

机译:网格分割算法客观评估的新方法

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摘要

3D segmentation methods and their evaluation are important problems in computer graphics. Many 3D segmentation techniques are available in the literature, how to efficiently evaluate these methods is an important issue. In this paper we propose a new objective evaluation metric suitable for the evaluation of 3D segmentation methods, based on the Dice Coefficient (DC). Dice Coefficient is a similarity coefficient, designed to compute the degree of similarity between sample data sets. We extend this approach to mesh segmentation evaluation, since the regions of a segmented mesh can be seen as sample data sets. Many of the existing metrics does not take into consideration the irregularity of the 3D meshes, our proposal integrate the surface of faces in the adaptation of the Dice Coefficient to evaluate the segmentation of both regular and irregular meshes. Experimental results confirm the potential of the proposed metric.
机译:3D分割方法及其评估是计算机图形学中的重要问题。文献中有许多3D分割技术,如何有效地评估这些方法是一个重要的问题。在本文中,我们基于骰子系数(DC)提出了一种适用于3D分割方法评估的新客观评估指标。骰子系数是一个相似系数,旨在计算样本数据集之间的相似度。我们将这种方法扩展到网格分割评估中,因为可以将分割网格的区域视为样本数据集。现有的许多度量标准都没有考虑3D网格的不规则性,我们的建议是将面的表面整合到Dice系数的适应中,以评估规则和不规则网格的分割。实验结果证实了拟议指标的潜力。

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