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ANEW MULTI-LEVEL ATTRIBUTED GRAPH BASED SHAPE MATCHING APPROACH TO COMPLEX TEMPLATE DESIGN FEATURE RECOGNITION

机译:基于多级归属图的复杂模板设计功能识别的形状匹配方法

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Some 3D complex shapes such as stair and compound-hole in engineering design always contains various geometric face types, adjacent geometric constraints and typical design semantics. These 3D shapes can be defined as template design features because they are frequently reused for synchronous shape modeling to greatly accelerate design and analysis process. To recognize the complex template design features, we present a new multi-level attributed graph based shape matching approach. The core idea is the Multi-level Attributed Graph (MLAG), which describes not only the geometry face types such as plane and the geometry relationships between two adjacent faces such as tangency that are usually used for 3D shape retrieval and manufacturing feature recognition, but also the design semantic features among multiple adjacent faces even non-adjacent faces such as boss. Such design semantic feature will greatly benefit MLAG matching process, so that a complex template design feature can be efficiently recognized for design modification. Finally, two experiments with some kinds of template feature recognition are also shown to demonstrate the effectiveness of the proposed method.
机译:一些3D复杂形状,如工程设计中的楼梯和复合孔始终包含各种几何面部类型,相邻的几何约束和典型的设计语义。这些3D形状可以定义为模板设计功能,因为它们经常重复使用同步形状建模,以大大加速设计和分析过程。要识别复杂的模板设计功能,我们介绍了一种基于多级归属图的形状匹配方法。核心思想是多级归属图(MLAG),其不仅描述了诸如平面的几何面部类型和两个相邻面之间的几何关系,例如正方形,通常用于3D形状检索和制造特征识别,但是此外,多个相邻面之间的设计语义特征甚至是诸如老板的非相邻面。这种设计语义特征将极大地利用MLAG匹配过程,从而可以有效地识别复杂的模板设计功能以进行设计修改。最后,还显示了两种具有某种模板特征识别的实验来证明所提出的方法的有效性。

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