An improved active shape model: Handling occlusion and outliers

  • Nicolae Duta
  • Milan Sonka
Session 6: Matching & Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)

Abstract

An improvement of the Active Shape procedure identifying new examples of previously learned shapes using the point distribution model is presented. The novel segmentation and interpretation approach incorporates a priori knowledge about the objects of interest and their specific structural relationships to provide robust segmentation and labeling.

The method was utilized to successfully identify 10 neuroanatomic structures in 19 individual MR images and 2 car classes (left-right and right-left oriented) in 400 perspective images of street scenes.

Keywords

Outlier Detection Shape Model Active Shape Model Outlier Removal Perspective Image 
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 1997

Authors and Affiliations

  • Nicolae Duta
    • 1
  • Milan Sonka
    • 2
  1. 1.Department of Computer ScienceMichigan State UniversityEast Lansing
  2. 2.Department of Electrical and Computer EngineeringThe University of IowaIowa City

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