Anatomically Correct Surface Recovery: A Statistical Approach

  • Rasmus R. Jensen
  • Jannik B. Nielsen
  • Rasmus Larsen
  • Rasmus R. Paulsen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9127)


We present a method for 3D surface recovery in partial surface scans. The method is based on an Active Shape Model, which is used to predict missing data. The model is constructed using a bootstrap framework, where an initially small collection of hand-annotated samples is used to fit to and register unknown samples, resulting in an extensive statistical model. The statistical recovery uses a multivariate point prediction, where the distribution of the points is given by the Active Shape Model. We show how missing data in a partial scan, once point correspondence is achieved, can be predicted using the learned statistics. A quantitative evaluation is performed on a data set of 10 laser scans of ear canal impressions with minimal noise and artificial holes. We also present a qualitative evaluation on authentic partial scans from an actual direct in ear scanner prototype. Compared to a state-of-the-art surface reconstruction algorithm, the presented method gives matching prediction results for the synthetic evaluation samples and superior results for the direct scanner data.


Surface recovery Hole closing Multivariate statistics Shape modeling In ear scanning Active shape model 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Rasmus R. Jensen
    • 1
  • Jannik B. Nielsen
    • 1
  • Rasmus Larsen
    • 1
  • Rasmus R. Paulsen
    • 1
  1. 1.DTU ComputeTechnical University of DenmarkKgs. LyngbyDenmark

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