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A markov random field model and method to image matching
Joint Authors
Ouali, Muhammad
Lange, Holger
Bouazz, Khayr al-Din
Source
The International Arab Journal of Information Technology
Issue
Vol. 9, Issue 6 (30 Nov. 2012)9 p.
Publisher
Publication Date
2012-11-30
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
In this paper, the correspondence problem is solved by minimizing an energy functional using a stochastic approach.
Our procedure generally follows G-man and German's Gibbs sampler for Markov Random Fields (MRF).
We propose a transition generator to generate and explore states.
The generator allows constraints such as unipolar, uniqueness, and order to be imposed.
We also propose to embed occlusions in the model.
The energy functional is designed to take into account resemblance, continuity, and number of occlusions.
The disparity and occlusion maps as modeled by their energy functional, i.e., as a Gibbs-Boltzmann distribution, are viewed as a MRF where the matching solution is an optimal state.
American Psychological Association (APA)
Ouali, Muhammad& Lange, Holger& Bouazz, Khayr al-Din. 2012. A markov random field model and method to image matching. The International Arab Journal of Information Technology،Vol. 9, no. 6.
https://search.emarefa.net/detail/BIM-305072
Modern Language Association (MLA)
Ouali, Muhammad…[et al.]. A markov random field model and method to image matching. The International Arab Journal of Information Technology Vol. 9, no. 6 (Nov. 2012).
https://search.emarefa.net/detail/BIM-305072
American Medical Association (AMA)
Ouali, Muhammad& Lange, Holger& Bouazz, Khayr al-Din. A markov random field model and method to image matching. The International Arab Journal of Information Technology. 2012. Vol. 9, no. 6.
https://search.emarefa.net/detail/BIM-305072
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references.
Record ID
BIM-305072