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Efficient MRF Deformation Model for Image Matching

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F06%3A03124647" target="_blank" >RIV/68407700:21230/06:03124647 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Efficient MRF Deformation Model for Image Matching

  • Original language description

    We propose a novel MRF-based model for image matching. Given two images, the task is to estimate a mapping from one image to another, in order to maximize the matching quality. We consider mappings defined by discrete deformation field constrained to preserve 2-dimensional continuity. We approach the corresponding optimization problem by the TRW-S (sequential Tree-reweighted message passing) algorithm [Wainwright-03, Kolmogorov-05]. Our model design allows for a considerably wider class of natural transformation and yields a compact representation of the optimization task. For this model TRW-S algorithm demonstrated nice practical performance on our experiments. We also propose a concise derivation of the TRW-S algorithm as a sequential maximization ofthe lower bound on the energy function.

  • Czech name

    Efficient MRF Deformation Model for Image Matching

  • Czech description

    We propose a novel MRF-based model for image matching. Given two images, the task is to estimate a mapping from one image to another, in order to maximize the matching quality. We consider mappings defined by discrete deformation field constrained to preserve 2-dimensional continuity. We approach the corresponding optimization problem by the TRW-S (sequential Tree-reweighted message passing) algorithm [Wainwright-03, Kolmogorov-05]. Our model design allows for a considerably wider class of natural transformation and yields a compact representation of the optimization task. For this model TRW-S algorithm demonstrated nice practical performance on our experiments. We also propose a concise derivation of the TRW-S algorithm as a sequential maximization ofthe lower bound on the energy function.

Classification

  • Type

    O - Miscellaneous

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/1M0567" target="_blank" >1M0567: Centre for Applied Cybernetics</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2006

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů