Making the most of using depth reasoning to label line drawings of engineering objects

Making the most of using depth reasoning to label line drawings of engineering objects
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DOI:
10.2312/sm.20041390
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发表时间:
2004-06
期刊:
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通讯作者:
Peter Ashley Clifford Varley;R. Martin;H. Suzuki
Peter Ashley Clifford Varley;R. Martin;H. Suzuki
中科院分区:
其他
文献类型:
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作者:
Peter Ashley Clifford Varley;R. Martin;H. Suzuki

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根据手绘草图自动创建工程对象的 B-rep 模型将使设计人员受益。子目标是绘制单线图(删除隐藏线),并从中推断出对象可见部分的初始 3D 几何实现。交汇点和线路标签以及临时深度坐标是该正面几何的重要组成部分。大多数生成正面几何图形的方法都使用线标记,但这很少或根本不考虑几何图形。因此,生成的线标签可能不可靠。之前,我们提出了一种方法,通过膨胀绘图来生成临时深度坐标,并使用它们来推论线标签。在某些情况下,即使是简单的实现也可以优于以前的行标记方法。在本文中,我们进一步增强了这种方法。我们将算法扩展到非等角投影绘图,考虑实现某些概念的改进方法,并考虑如何将此方法与其他标记技术结合起来以获得每种技术的好处。我们使用我们认为具有代表性的工程对象样本的绘图来测试我们的方法;这些例证了许多以前的在线标签论文中没有考虑到的困难。我们基于该测试集的结果表明,这些增强功能带来了显着的好处。
Automatic creation of B-rep models of engineering objects from freehand sketches would benefit designers. A subgoal is to take a single line drawing (with hidden lines removed), and from it deduce an initial 3D geometric realisation of the visible part of the object. Junction and line labels, and provisional depth coordinates, are important components of this frontal geometry. Most methods for producing frontal geometry use line labelling, but this takes little or no account of geometry. As a result, the line labels produced can be unreliable.Previously, we proposed an approach which inflates a drawing to produce provisional depth coordinates, and uses these to make deductions about line labels. Even a naïve implementation can outperform previous line labelling methods in certain cases. In this paper, we further enhance this approach. We extend the algorithm to non-isometric-projection drawings, consider improved ways of realising some of the concepts, and also consider how to combine this approach with other labelling techniques to gain the benefits of each.We test our approach using to be drawings of what we consider representative samples of engineering objects; these exemplify difficulties not considered in many previous papers on line labelling. Our results, based on this test set, show that the enhancements result in significant benefits.