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Cited by 447

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Parallel and deterministic algorithms from MRFs: surface reconstruction

Geiger, D., Girosi, F.·1991·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

Deterministic approximations to Markov random field (MRF) models are derived. One of the models is shown to give in a natural way the graduated nonconvexity (GNC) algorithm proposed by A. Blake and A. Zisserman (1987). This model can be applied to smooth a field preserving its discontinuities. A class of more complex models is then proposed in order to deal with a variety of vision problems. All the theoretical results are obtained in the framework of statistical mechanics and mean field techniques. A parallel, iterative algorithm to solve the deterministic equations of the two models is presented, together with some experiments on synthetic and real images.>

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Metadata

Authors
Geiger, D., & Girosi, F.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
1991-05
Volume
13
Issue
5
Pages
401-412
ISSN
0162-8828 (ISSN-L)
OpenAlex
W2020278873
Cited by
447
References
14
FWCI
32.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Parallel and deterministic algorithms from MRFs: surface reconstruction. https://app.cochat.ai/papers/10.1109/34.134040
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Geiger, D., & Girosi, F. (1991). Parallel and deterministic algorithms from MRFs: surface reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.134040

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