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Contour people: A parameterized model of {2D} articulated human shape

2010

Conference Paper

ps


We define a new “contour person” model of the human body that has the expressive power of a detailed 3D model and the computational benefits of a simple 2D part-based model. The contour person (CP) model is learned from a 3D SCAPE model of the human body that captures natural shape and pose variations; the projected contours of this model, along with their segmentation into parts forms the training set. The CP model factors deformations of the body into three components: shape variation, viewpoint change and part rotation. This latter model also incorporates a learned non-rigid deformation model. The result is a 2D articulated model that is compact to represent, simple to compute with and more expressive than previous models. We demonstrate the value of such a model in 2D pose estimation and segmentation. Given an initial pose from a standard pictorial-structures method, we refine the pose and shape using an objective function that segments the scene into foreground and background regions. The result is a parametric, human-specific, image segmentation.

Author(s): Freifeld, O. and Weiss, A. and Zuffi, S. and Black, M. J.
Book Title: IEEE Conf. on Computer Vision and Pattern Recognition, (CVPR)
Pages: 639--646
Year: 2010
Month: June
Publisher: IEEE

Department(s): Perceiving Systems
Research Project(s): Deformable Structures
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

Links: pdf
slides
video of CVPR talk

BibTex

@inproceedings{Freifeld:CVPR:10,
  title = {Contour people: A parameterized model of {2D} articulated human shape},
  author = {Freifeld, O. and Weiss, A. and Zuffi, S. and Black, M. J.},
  booktitle = {IEEE Conf. on Computer Vision and Pattern Recognition, (CVPR)},
  pages = {639--646},
  publisher = {IEEE},
  month = jun,
  year = {2010},
  month_numeric = {6}
}