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  Global Connectivity Potentials for Random Field Models

Nowozin, S., & Lampert, C. (2009). Global Connectivity Potentials for Random Field Models. In 2009 IEEE Conference on Computer Vision and Pattern Recognition (pp. 818-825). Piscataway, NJ, USA: IEEE Service Center.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-C47F-B Version Permalink: http://hdl.handle.net/21.11116/0000-0002-F8F7-0
Genre: Conference Paper

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 Creators:
Nowozin, S1, 2, Author              
Lampert, CH1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions and cannot model global properties, such as connectedness, which is a potentially useful high-level prior for object segmentation. In this work, we overcome this limitation by deriving a potential function that enforces the output labeling to be connected and that can naturally be used in the framework of recent MAP-MRF LP relaxations. Using techniques from polyhedral combinatorics, we show that a provably tight approximation to the MAP solution of the resulting MRF can still be found efficiently by solving a sequence of max-flow problems. The efficiency of the inference procedure also allows us to learn the parameters of a MRF with global connectivity potentials by means of a cutting plane algorithm. We experimentally evaluate our algorithm on both synthetic data and on the challenging segmentation task of the PASCAL VOC 2008 data set. We show that in both cases the addition of a connectedness prior significantly reduces the segmentation error.

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 Dates: 2009-06
 Publication Status: Published in print
 Pages: -
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 Rev. Method: -
 Identifiers: DOI: 10.1109/CVPRW.2009.5206567
BibTex Citekey: 5828
 Degree: -

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Title: IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Place of Event: Miami Beach, FL, USA
Start-/End Date: 2009-06-20 - 2009-06-25

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Title: 2009 IEEE Conference on Computer Vision and Pattern Recognition
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE Service Center
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 818 - 825 Identifier: -