Structure-adaptive shape editing for man-made objects

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

9 Scopus Citations
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Original languageEnglish
Pages (from-to)27-36
Journal / PublicationComputer Graphics Forum
Volume35
Issue number2
Online published27 May 2016
Publication statusPublished - May 2016

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Abstract

One of the challenging problems for shape editing is to adapt shapes with diversified structures for various editing needs. In this paper we introduce a shape editing approach that automatically adapts the structure of a shape being edited with respect to user inputs. Given a category of shapes, our approach first classifies them into groups based on the constituent parts. The group-sensitive priors, including both inter-group and intra-group priors, are then learned through statistical structure analysis and multivariate regression. By using these priors, the inherent characteristics and typical variations of shape structures can be well captured. Based on such group-sensitive priors, we propose a framework for real-time shape editing, which adapts the structure of shape to continuous user editing operations. Experimental results show that the proposed approach is capable of both structure-preserving and structure-varying shape editing.

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Structure-adaptive shape editing for man-made objects. / Fu, Qiang; Chen, Xiaowu; Su, Xiaoyu; Li, Jia; Fu, Hongbo.

In: Computer Graphics Forum, Vol. 35, No. 2, 05.2016, p. 27-36.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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