自适应网格构造的边缘提取

R. Miyazaki, K. Harada
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引用次数: 1

摘要

我们提出了一种从距离数据中提取物体锐利边缘的方法,以创建自适应网格模型。到目前为止,当从距离数据创建自适应网格模型时,我们提取的是具有重要特征的点,如物体的高曲率点。人类视觉系统在很大程度上依赖于锐利的边缘来识别物体。因此,在创建自适应网格模型时,应该保留对象的锐边位置。锐边是通过网格模型中点的连通性来表示的。我们的方法直接处理连接信息来创建网格模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Edge extraction for adaptive mesh construction
We propose the method of extracting sharp edges of an object from range data in order to create an adaptive mesh model. So far, when an adaptive mesh model is created from range data, we extract points that present important features such as high curvature points of an object. The human vision system relies heavily on sharp edges to recognize objects. So the location of sharp edges of an object should be retained as well when creating an adaptive mesh model. Sharp edges are expressed by the connectivity of points in a mesh model. Our method handles directly the information of the connectivity to create the mesh model.
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