A Privacy Algorithm for 3D Human Body Scans

  • Joseph Laws
  • Yang Cai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3994)


In this paper, we explore a privacy algorithm that detects human private parts in a 3D scan dataset. The intrinsic human proportions are applied to reduce the search space by an order of magnitude. A feature shape template is constructed to match the model data points using Radial Basis Functions in a non-linear regression. The feature is then detected using the relative measurements of the height and area factors. The method is tested on 100 datasets from CAESER database.


Radial Basis Function Template Match Curvature Feature Body Feature Privacy Algorithm 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Joseph Laws
    • 1
  • Yang Cai
    • 1
  1. 1.Visual Intelligence Studio, Cylab, CIC 2218Carnegie Mellon UniversityPittsburghUSA

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