• 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