Header logo is ps

The naked truth: Estimating body shape under clothing,


Conference Paper


We propose a method to estimate the detailed 3D shape of a person from images of that person wearing clothing. The approach exploits a model of human body shapes that is learned from a database of over 2000 range scans. We show that the parameters of this shape model can be recovered independently of body pose. We further propose a generalization of the visual hull to account for the fact that observed silhouettes of clothed people do not provide a tight bound on the true 3D shape. With clothed subjects, different poses provide different constraints on the possible underlying 3D body shape. We consequently combine constraints across pose to more accurately estimate 3D body shape in the presence of occluding clothing. Finally we use the recovered 3D shape to estimate the gender of subjects and then employ gender-specific body models to refine our shape estimates. Results on a novel database of thousands of images of clothed and "naked" subjects, as well as sequences from the HumanEva dataset, suggest the method may be accurate enough for biometric shape analysis in video.

Author(s): Balan, A. and Black, M. J.
Book Title: European Conf. on Computer Vision, ECCV
Volume: 5304
Pages: 15--29
Year: 2008
Month: October

Series: LNCS
Editors: D. Forsyth and P. Torr and A. Zisserman
Publisher: Springer-Verlag

Department(s): Perceiving Systems
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

Address: Marseilles, France

Links: pdf
pdf with higher quality images
Springerlink version
video on applications
Attachments: slides


  title = {The naked truth: Estimating body shape under clothing,},
  author = {Balan, A. and Black, M. J.},
  booktitle = {European Conf. on Computer Vision, ECCV},
  volume = {5304},
  pages = {15--29},
  series = {LNCS},
  editors = {D. Forsyth and P. Torr and A. Zisserman},
  publisher = {Springer-Verlag},
  address = {Marseilles, France},
  month = oct,
  year = {2008},
  month_numeric = {10}