The Naked Truth: Estimating Body Shape Under Clothing

  • Alexandru O. Bălan
  • Michael J. Black
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5303)


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.


Body Shape Visual Hull Image Silhouette Human Shape Foreground Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

978-3-540-88688-4_2_MOESM1_ESM.avi (23.1 mb)
Supplementary material (23,610 KB)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Alexandru O. Bălan
    • 1
  • Michael J. Black
    • 1
  1. 1.Department of Computer ScienceBrown University, ProvidenceUSA

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