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Model Selection for Range Segmentation of Curved Objects

  • Alireza Bab-Hadiashar
  • Niloofar Gheissari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3021)

Abstract

In the present paper, we address the problem of recovering the true underlying model of a surface while performing the segmentation. A novel criterion for surface (model) selection is introduced and its performance for selecting the underlying model of various surfaces has been tested and compared with many other existing techniques. Using this criterion, we then present a range data segmentation algorithm capable of segmenting complex objects with planar and curved surfaces. The algorithm simultaneously identifies the type (order and geometric shape) of surface and separates all the points that are part of that surface from the rest in a range image. The paper includes the segmentation results of a large collection of range images obtained from objects with planar and curved surfaces.

Keywords

Curve Surface Segmentation Algorithm Segmentation Result Machine Intelligence Range Data 
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 2004

Authors and Affiliations

  • Alireza Bab-Hadiashar
    • 1
  • Niloofar Gheissari
    • 1
  1. 1.School of Engineering & ScienceSwinburne University of TechnologyMelbourneAustralia

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