A privacy algorithm for 3d human body scans

  • Authors:
  • Joseph Laws;Yang Cai

  • Affiliations:
  • Visual Intelligence Studio, Cylab, CIC 2218, Carnegie Mellon University, Pittsburgh, PA;Visual Intelligence Studio, Cylab, CIC 2218, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
  • Year:
  • 2006

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Abstract

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.