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International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition

EMMCVPR 2009: Energy Minimization Methods in Computer Vision and Pattern Recognition pp 70–83Cite as

Parallel Hidden Hierarchical Fields for Multi-scale Reconstruction

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5681))

Abstract

In any problem involving images having scale-dependent structures, a key issue is the modeling of these multi-scale characteristics. Because multi-scale phenomena frequently possess nonstationary, piece-wise multi-model behaviour, the classic hidden Markov method can not perform well in modeling such complex images. In this paper we provide a new modeling approach to extend previous hierarchical methods, with multiple hidden fields, to perform reconstruction in more complex, nonstationary contexts.

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Author information

Authors and Affiliations

  1. Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1

    Ying Liu & Paul Fieguth

Authors
  1. Ying Liu
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  2. Paul Fieguth
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Editor information

Editors and Affiliations

  1. Institut für Informatik III, Rö, Universität Bonn, merstraße 164, 53117, Bonn, Germany

    Daniel Cremers

  2. Computer Science Department, University of Western Ontario, N6A 5A5, London, ON, Canada

    Yuri Boykov

  3. Microsoft Research, J.J. Thomson Avenue, CB3 OFB, Cambridge, United Kingdom

    Andrew Blake

  4. Institut für Informatik III, Universität Bonn, Römerstraße 164, 53117, Bonn, Germany

    Frank R. Schmidt

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© 2009 Springer-Verlag Berlin Heidelberg

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Liu, Y., Fieguth, P. (2009). Parallel Hidden Hierarchical Fields for Multi-scale Reconstruction. In: Cremers, D., Boykov, Y., Blake, A., Schmidt, F.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2009. Lecture Notes in Computer Science, vol 5681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03641-5_6

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  • DOI: https://doi.org/10.1007/978-3-642-03641-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03640-8

  • Online ISBN: 978-3-642-03641-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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