3D mesh pose transfer based on skeletal deformation

被引:2
作者
Yang, Shigeng [1 ]
Yin, Mengxiao [1 ,2 ,4 ]
Li, Ming [1 ]
Li, Guiqing [3 ]
Chang, Kan [1 ,2 ]
Yang, Feng [1 ,2 ]
机构
[1] Guangxi Univ, Sch Comp Elect & Informat, Nanning, Guangxi, Peoples R China
[2] Guangxi Univ, Guangxi Key Lab Multimedia Commun Network Technol, Nanning, Guangxi, Peoples R China
[3] South China Univ Technol, Sch Comp Sci & Engn, Guangzhou, Guangdong, Peoples R China
[4] Guangxi Univ, Sch Comp Elect & Informat, Nanning 530004, Guangxi, Peoples R China
基金
中国国家自然科学基金;
关键词
deep learning; pose transfer; skeleton extraction; skinning deformation;
D O I
10.1002/cav.2156
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
For 3D mesh pose transfer, the target model is obtained by transferring the pose of the reference mesh to the source mesh, where the shape and pose of the source are usually different from that of the reference. In this paper, pose transfer is considered as a deformation process of the source mesh, and we propose a 3D mesh pose transfer method based on skeletal deformation. First, we design a neural network based on the edge convolution operator to extract the skeleton of the 3D mesh and bind the rigid weights; then, we calculate the bone transformations between the two skeletons with different poses and use the diffusion equation to smooth the rigid weights; finally, the source mesh is deformed according to the bone transformations and the smooth weights to get the target mesh. Experiment results on different datasets show that the pose of the reference mesh can be effectively transferred to the source one while maintaining the shape and high-quality geometric details of the source mesh by using our method.
引用
收藏
页数:14
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