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Data‐Driven Shape Interpolation and Morphing Editing
Author(s) -
Gao Lin,
Chen ShuYu,
Lai YuKun,
Xia Shihong
Publication year - 2017
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12991
Subject(s) - morphing , computer science , interpolation (computer graphics) , computer animation , computer graphics , computer graphics (images) , animation , computer vision , invariant (physics) , representation (politics) , linear interpolation , translation (biology) , artificial intelligence , algorithm , pattern recognition (psychology) , mathematics , biochemistry , chemistry , politics , messenger rna , political science , law , mathematical physics , gene
Abstract Shape interpolation has many applications in computer graphics such as morphing for computer animation. In this paper, we propose a novel data‐driven mesh interpolation method. We adapt patch‐based linear rotational invariant coordinates to effectively represent deformations of models in a shape collection, and utilize this information to guide the synthesis of interpolated shapes. Unlike previous data‐driven approaches, we use a rotation/translation invariant representation which defines the plausible deformations in a global continuous space. By effectively exploiting the knowledge in the shape space, our method produces realistic interpolation results at interactive rates, outperforming state‐of‐the‐art methods for challenging cases. We further propose a novel approach to interactive editing of shape morphing according to the shape distribution. The user can explore the morphing path and select example models intuitively and adjust the path with simple interactions to edit the morphing sequences. This provides a useful tool to allow users to generate desired morphing with little effort. We demonstrate the effectiveness of our approach using various examples.