• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

Efficient Variants of the ICP Algorithm (2001)

Cached

  • Download as a PDF

Download Links

  • [www.cs.princeton.edu]
  • [graphics.stanford.edu]
  • [www.cs.princeton.edu:80]
  • [www.cs.princeton.edu]
  • [www.cs.jhu.edu]
  • [www.cs.uni-bonn.de]
  • [www-graphics.stanford.edu]
  • [www.cs.hunter.cuny.edu]
  • [web.eecs.umich.edu]
  • [graphics.stanford.edu]
  • [www.tecgraf.puc-rio.br]
  • [www.cvl.iis.u-tokyo.ac.jp]
  • [docs.happycoders.org]
  • [www.cs.jhu.edu]
  • [www.cs.princeton.edu]
  • [www.cvl.iis.u-tokyo.ac.jp]
  • [www.tecgraf.puc-rio.br]
  • [web.eecs.umich.edu]
  • [www.cs.hunter.cuny.edu]
  • [webserver2.tecgraf.puc-rio.br]

  • Other Repositories/Bibliography

  • DBLP
  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Szymon Rusinkiewicz , Marc Levoy
Venue:INTERNATIONAL CONFERENCE ON 3-D DIGITAL IMAGING AND MODELING
Citations:718 - 5 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@INPROCEEDINGS{Rusinkiewicz01efficientvariants,
    author = {Szymon Rusinkiewicz and Marc Levoy},
    title = {Efficient Variants of the ICP Algorithm},
    booktitle = {INTERNATIONAL CONFERENCE ON 3-D DIGITAL IMAGING AND MODELING},
    year = {2001},
    publisher = {}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minimization strategy. We enumerate and classify many of these variants, and evaluate their effect on the speed with which the correct alignment is reached. In order to improve convergence for nearly-flat meshes with small features, such as inscribed surfaces, we introduce a new variant based on uniform sampling of the space of normals. We conclude by proposing a combination of ICP variants optimized for high speed. We demonstrate an implementation that is able to align two range images in a few tens of milliseconds, assuming a good initial guess. This capability has potential application to real-time 3D model acquisition and model-based tracking.

Keyphrases

icp algorithm    efficient variant    minimization strategy    range image    geometric alignment    relative pose    three-dimensional model    initial estimate    uniform sampling    new variant    model acquisition    high speed    nearly-flat mesh    icp variant    small feature    correct alignment    many variant    model-based tracking    inscribed surface    potential application    good initial guess    iterative closest point   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University