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Sparse Data Driven Mesh Deformation

文献类型：期刊论文

作者Gao, Lin2; Lai, Yu-Kun1; Yang, Jie2; Zhang, Ling-Xiao2; Xia, Shihong2; Kobbelt, Leif3
刊名IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
出版日期2021-03-01
卷号27期号:3页码:2085-2100
ISSN号1077-2626
关键词Strain Shape Deformable models Interpolation Computational modeling Geometry Manifolds Data driven sparsity large scale deformation real-time deformation
DOI10.1109/TVCG.2019.2941200
英文摘要Example-based mesh deformation methods are powerful tools for realistic shape editing. However, existing techniques typically combine all the example deformation modes, which can lead to overfitting, i.e., using an overly complicated model to explain the user-specified deformation. This leads to implausible or unstable deformation results, including unexpected global changes outside the region of interest. To address this fundamental limitation, we propose a sparse blending method that automatically selects a smaller number of deformation modes to compactly describe the desired deformation. This along with a suitably chosen deformation basis including spatially localized deformation modes leads to significant advantages, including more meaningful, reliable, and efficient deformations because fewer and localized deformation modes are applied. To cope with large rotations, we develop a simple but effective representation based on polar decomposition of deformation gradients, which resolves the ambiguity of large global rotations using an as-consistent-as-possible global optimization. This simple representation has a closed form solution for derivatives, making it efficient for our sparse localized representation and thus ensuring interactive performance. Experimental results show that our method outperforms state-of-the-art data-driven mesh deformation methods, for both quality of results and efficiency.
资助项目Beijing Municipal Natural Science Foundation[L182016] ; National Natural Science Foundation of China[61872440] ; National Natural Science Foundation of China[61828204] ; Youth Innovation Promotion Association CAS ; Young Elite Scientists Sponsorship Program by CAST[2017QNRC001] ; CCF-Tencent Open Fund ; SenseTime Research Fund ; Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University[VRLAB2019C01]
WOS研究方向Computer Science
语种英语
出版者IEEE COMPUTER SOC
WOS记录号WOS:000613744500016
源URL[http://119.78.100.204/handle/2XEOYT63/16257]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Gao, Lin
作者单位1.Cardiff Univ, Sch Comp Sci & Informat, Visual Comp Grp, Cardiff CF10 3AT, Wales
2.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China
3.Rhein Westfal TH Aachen, Inst Comp Graph & Multimedia, D-52062 Aachen, Germany
推荐引用方式
GB/T 7714		 Gao, Lin,Lai, Yu-Kun,Yang, Jie,et al. Sparse Data Driven Mesh Deformation[J]. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS,2021,27(3):2085-2100.
APA Gao, Lin,Lai, Yu-Kun,Yang, Jie,Zhang, Ling-Xiao,Xia, Shihong,&Kobbelt, Leif.(2021).Sparse Data Driven Mesh Deformation.IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS,27(3),2085-2100.
MLA Gao, Lin,et al."Sparse Data Driven Mesh Deformation".IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 27.3(2021):2085-2100.

入库方式： OAI收割

来源：计算技术研究所

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