Markov random fields on triangle meshes

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Standard

Markov random fields on triangle meshes. / Andersen, Vedrana; Aanæs, Henrik; Bærentzen, Jakob Andreas; Nielsen, Mads.

WSCG 2010: communication papers proceedings . red. / Vaclav Skala. Vaclav Skala - Union Agency, 2010. s. 265-270.

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Harvard

Andersen, V, Aanæs, H, Bærentzen, JA & Nielsen, M 2010, Markov random fields on triangle meshes. i V Skala (red.), WSCG 2010: communication papers proceedings . Vaclav Skala - Union Agency, s. 265-270, 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, Plzen, Tjekkiet, 01/02/2010.

APA

Andersen, V., Aanæs, H., Bærentzen, J. A., & Nielsen, M. (2010). Markov random fields on triangle meshes. I V. Skala (red.), WSCG 2010: communication papers proceedings (s. 265-270). Vaclav Skala - Union Agency.

Vancouver

Andersen V, Aanæs H, Bærentzen JA, Nielsen M. Markov random fields on triangle meshes. I Skala V, red., WSCG 2010: communication papers proceedings . Vaclav Skala - Union Agency. 2010. s. 265-270

Author

Andersen, Vedrana ; Aanæs, Henrik ; Bærentzen, Jakob Andreas ; Nielsen, Mads. / Markov random fields on triangle meshes. WSCG 2010: communication papers proceedings . red. / Vaclav Skala. Vaclav Skala - Union Agency, 2010. s. 265-270

Bibtex

@inproceedings{0d6aaf10260d11df8ed1000ea68e967b,
title = "Markov random fields on triangle meshes",
abstract = "In this paper we propose a novel anisotropic smoothing scheme based on Markov Random Fields (MRF). Our scheme is formulated as two coupled processes. A vertex process is used to smooth the mesh by displacing the vertices according to a MRF smoothness prior, while an independent edge process labels mesh edges according to a feature detecting prior. Since we should not smooth across a sharp feature, we use edge labels to control the vertex process. In a Bayesian framework, MRF priors are combined with the likelihood function related to the mesh formation method. The output of our algorithm is a piecewise smooth mesh with explicit labelling of edges belonging to the sharp features.",
author = "Vedrana Andersen and Henrik Aan{\ae}s and B{\ae}rentzen, {Jakob Andreas} and Mads Nielsen",
year = "2010",
language = "English",
isbn = "978-80-86943-87-9",
pages = "265--270",
editor = "Vaclav Skala",
booktitle = "WSCG 2010",
publisher = "Vaclav Skala - Union Agency",
note = "18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 ; Conference date: 01-02-2010 Through 04-02-2010",

}

RIS

TY - GEN

T1 - Markov random fields on triangle meshes

AU - Andersen, Vedrana

AU - Aanæs, Henrik

AU - Bærentzen, Jakob Andreas

AU - Nielsen, Mads

N1 - Conference code: 18

PY - 2010

Y1 - 2010

N2 - In this paper we propose a novel anisotropic smoothing scheme based on Markov Random Fields (MRF). Our scheme is formulated as two coupled processes. A vertex process is used to smooth the mesh by displacing the vertices according to a MRF smoothness prior, while an independent edge process labels mesh edges according to a feature detecting prior. Since we should not smooth across a sharp feature, we use edge labels to control the vertex process. In a Bayesian framework, MRF priors are combined with the likelihood function related to the mesh formation method. The output of our algorithm is a piecewise smooth mesh with explicit labelling of edges belonging to the sharp features.

AB - In this paper we propose a novel anisotropic smoothing scheme based on Markov Random Fields (MRF). Our scheme is formulated as two coupled processes. A vertex process is used to smooth the mesh by displacing the vertices according to a MRF smoothness prior, while an independent edge process labels mesh edges according to a feature detecting prior. Since we should not smooth across a sharp feature, we use edge labels to control the vertex process. In a Bayesian framework, MRF priors are combined with the likelihood function related to the mesh formation method. The output of our algorithm is a piecewise smooth mesh with explicit labelling of edges belonging to the sharp features.

M3 - Article in proceedings

SN - 978-80-86943-87-9

SP - 265

EP - 270

BT - WSCG 2010

A2 - Skala, Vaclav

PB - Vaclav Skala - Union Agency

T2 - 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision

Y2 - 1 February 2010 through 4 February 2010

ER -

ID: 18339850