Component‐wise Controllers for Structure‐Preserving Shape Manipulation

Component‐wise Controllers for Structure‐Preserving Shape Manipulation
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DOI:
10.1111/j.1467-8659.2011.01880.x
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发表时间:
2011-04
影响因子:
2.5
通讯作者:
Youyi Zheng;Hongbo Fu;D. Cohen-Or;Oscar Kin-Chung Au;Chiew-Lan Tai
Youyi Zheng;Hongbo Fu;D. Cohen-Or;Oscar Kin-Chung Au;Chiew-Lan Tai
中科院分区:
计算机科学4区
文献类型:
--
作者:
Youyi Zheng;Hongbo Fu;D. Cohen-Or;Oscar Kin-Chung Au;Chiew-Lan Tai

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最近的形状编辑技术,特别是对于人造模型,已经逐渐将重点从维护局部,低层次的几何特征转移到保留结构,高层次的特征,如对称性和平行性。这种新的编辑目标通常需要预处理形状分析步骤以实现后续形状编辑。观察到大多数形状的编辑都涉及操纵其组成组件,我们引入了组件控制器,这些控制器适用于从形状分析中推断出的组件特性。控制器捕捉各个组件的自然自由度,从而提供直观的用户界面进行编辑。一个典型的模型通常会导致一个中等数量的控制器,允许很容易建立它们之间的语义关系,通过自动形状分析与用户交互补充。我们提出了一个组件式传播算法,以自动保留已建立的相互关系,同时保持单个控制器的定义特性,并尊重用户指定的建模约束。我们将这些想法扩展到分层设置,允许用户根据所需的建模复杂性调整工具复杂性。我们证明了我们的技术在各种具有结构特征的人造模型上的有效性,这些模型通常包含多个连接件。
Recent shape editing techniques, especially for man‐made models, have gradually shifted focus from maintaining local, low‐level geometric features to preserving structural, high‐level characteristics like symmetry and parallelism. Such new editing goals typically require a pre‐processing shape analysis step to enable subsequent shape editing. Observing that most editing of shapes involves manipulating their constituent components, we introduce component‐wise controllers that are adapted to the component characteristics inferred from shape analysis. The controllers capture the natural degrees of freedom of individual components and thus provide an intuitive user interface for editing. A typical model usually results in a moderate number of controllers, allowing easy establishment of semantic relations among them by automatic shape analysis supplemented with user interaction. We propose a component‐wise propagation algorithm to automatically preserve the established inter‐relations while maintaining the defining characteristics of individual controllers and respecting the user‐specified modeling constraints. We extend these ideas to a hierarchical setup, allowing the user to adjust the tool complexity with respect to the desired modeling complexity. We demonstrate the effectiveness of our technique on a wide range of man‐made models with structural features, often containing multiple connected pieces.