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Recognition of Simple 3D Geometrical Objects under Partial Occlusion

  • Alexandra Barchunova
  • Gerald Sommer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5702)

Abstract

In this paper we present a novel procedure for contour-based recognition of partially occluded three-dimensional objects. In our approach we use images of real and rendered objects whose contours have been deformed by a restricted change of the viewpoint. The preparatory part consists of contour extraction, preprocessing, local structure analysis and feature extraction. The main part deals with an extended construction and functionality of the classifier ensemble Adaptive Occlusion Classifier (AOC). It relies on a hierarchical fragmenting algorithm to perform a local structure analysis which is essential when dealing with occlusions. In the experimental part of this paper we present classification results for five classes of simple geometrical figures: prism, cylinder, half cylinder, a cube, and a bridge. We compare classification results for three classical feature extractors: Fourier descriptors, pseudo Zernike and Zernike moments.

Keywords

Zernike Moment Partial Occlusion Fourier Descriptor Occlude Object Area Occlusion 
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 2009

Authors and Affiliations

  • Alexandra Barchunova
    • 1
  • Gerald Sommer
    • 1
  1. 1.Bielefeld UniversityBielefeldGermany

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