Title :
Tensor-Based Human Body Modeling
Author :
Yinpeng Chen ; Zicheng Liu ; Zhengyou Zhang
Author_Institution :
Microsoft Res., Redmond, WA, USA
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;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location :
Portland, OR
DOI :
10.1109/CVPR.2013.21