DocumentCode
3327784
Title
Tensor-Based Human Body Modeling
Author
Yinpeng Chen ; Zicheng Liu ; Zhengyou Zhang
Author_Institution
Microsoft Res., Redmond, WA, USA
fYear
2013
fDate
23-28 June 2013
Firstpage
105
Lastpage
112
Abstract
In this paper, we present a novel approach to model 3D human body with variations on both human shape and pose, by exploring a tensor decomposition technique. 3D human body modeling is important for 3D reconstruction and animation of realistic human body, which can be widely used in Tele-presence and video game applications. It is challenging due to a wide range of shape variations over different people and poses. The existing SCAPE model is popular in computer vision for modeling 3D human body. However, it considers shape and pose deformations separately, which is not accurate since pose deformation is person-dependent. Our tensor-based model addresses this issue by jointly modeling shape and pose deformations. Experimental results demonstrate that our tensor-based model outperforms the SCAPE model quite significantly. We also apply our model to capture human body using Microsoft Kinect sensors with excellent results.
Keywords
computer animation; computer vision; image reconstruction; tensors; 3D human body modeling; 3D reconstruction; Microsoft Kinect sensors; SCAPE model; computer vision; human pose; human shape; pose deformations; realistic human body animation; tele-presence; tensor decomposition technique; tensor-based human body modeling; video game applications; Biological system modeling; Deformable models; Joints; Shape; Solid modeling; Three-dimensional displays; Vectors; Human Body Modeling; Tensor Decomposition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location
Portland, OR
ISSN
1063-6919
Type
conf
DOI
10.1109/CVPR.2013.21
Filename
6618865
Link To Document