Results 11 to 20 of about 47,039 (298)
Markov Random Field Surface Reconstruction [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2010 A method for implicit surface reconstruction is proposed. The novelty in this paper is the adaptation of Markov Random Field regularization of a distance field. The Markov Random Field formulation allows us to integrate both knowledge about the type of surface we wish to reconstruct (the prior) and knowledge about data (the observation model) in an ...
Rasmus R. Paulsen +2 more
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One-dimensional Markov random fields, Markov chains and topological Markov fields [PDF]
Proceedings of the American Mathematical Society, 2013 15 ...
Marcus, B +4 more
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Abstract Markov Random Fields [PDF]
CompositionalityMarkov random fields are known to be fully characterized by properties of their information diagrams, or I-diagrams. In particular, for Markov random fields, regions in the I-diagram corresponding to disconnected vertex sets in the graph vanish. Recently, I-diagrams have been generalized to F-diagrams, for a larger class of functions F satisfying the ...
Leon Lang +3 more
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Image Haze Removal Based on Superpixels and Markov Random Field
IEEE Access, 2020 Image haze removal is critical for autonomous driving. However, it is a challenging task for the existing image dehazing algorithms to eliminate the block effect completely and handle objects similar to light (such as snowy objects and white buildings ...
Yibo Tan, Guoyu Wang
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Remote Sensing, 2021 In this paper, a hierarchical probabilistic graphical model is proposed to tackle joint classification of multiresolution and multisensor remote sensing images of the same scene.
Martina Pastorino +6 more
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Factorial Markov Random Fields [PDF]
, 2002 In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous to the extension from Hidden Markov Models (HMM's) to Factorial HMM's. We present an efficient EM-based algorithm for inference on Factorial MRF's.
Junhwan Kim, Ramin Zabih
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A Markov random field image segmentation model for lizard spots
Revista Facultad de Ingeniería Universidad de Antioquia, 2016 Animal identification as a method for fauna study and conservation can be implemented using phenotypic appearance features such as spots, stripes or morphology. This procedure has the advantage that it does not harm study subjects.
Alexander Gómez-Villa +2 more
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Dim and Small Target Detection Based on Gaussian Markov Random Field Motion Direction Estimation
IEEE Access, 2022 To improve the detection of dim and small targets in low signal-to-noise ratio (SNR < 3dB) scenarios, energy accumulation along the estimated direction by estimating the direction of the target’s motion at different moments is a proven ...
Lei Min +4 more
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Combinatorial Markov Random Fields [PDF]
, 2006 A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatorial Markov random fields (Comrafs), which are Markov random fields where some of the nodes are combinatorial random variables.
Bekkerman, R +2 more
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Bottleneck Potentials in Markov Random Fields [PDF]
2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019 We consider general discrete Markov Random Fields(MRFs) with additional bottleneck potentials which penalize the maximum (instead of the sum) over local potential value taken by the MRF-assignment. Bottleneck potentials or analogous constructions have been considered in (i) combinatorial optimization (e.g.
Ahmed Abbas, Paul Swoboda
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