Tensor-Based Human Body Modeling

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 [4] 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 persondependent. 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.

Cite

Text

Chen et al. "Tensor-Based Human Body Modeling." Conference on Computer Vision and Pattern Recognition, 2013. doi:10.1109/CVPR.2013.21

Markdown

[Chen et al. "Tensor-Based Human Body Modeling." Conference on Computer Vision and Pattern Recognition, 2013.](https://mlanthology.org/cvpr/2013/chen2013cvpr-tensorbased/) doi:10.1109/CVPR.2013.21

BibTeX

@inproceedings{chen2013cvpr-tensorbased,
  title     = {{Tensor-Based Human Body Modeling}},
  author    = {Chen, Yinpeng and Liu, Zicheng and Zhang, Zhengyou},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2013},
  doi       = {10.1109/CVPR.2013.21},
  url       = {https://mlanthology.org/cvpr/2013/chen2013cvpr-tensorbased/}
}