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» The Complexity of Distinguishing Markov Random Fields
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TOG
2008
103views more  TOG 2008»
13 years 7 months ago
Sketch-based tree modeling using Markov random field
In this paper, we describe a new system for converting a user's freehand sketch of a tree into a full 3D model that is both complex and realistic-looking. Our system does thi...
Xuejin Chen, Boris Neubert, Ying-Qing Xu, Oliver D...
ICIP
2003
IEEE
14 years 8 months ago
Object localization using texture motifs and Markov random fields
This work presents a novel approach to object localization in complex imagery. In particular, the spatial extents of objects characterized by distinct spatial signatures at multip...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath
SIGECOM
2006
ACM
184views ECommerce» more  SIGECOM 2006»
14 years 29 days ago
Computing pure nash equilibria in graphical games via markov random fields
We present a reduction from graphical games to Markov random fields so that pure Nash equilibria in the former can be found by statistical inference on the latter. Our result, wh...
Constantinos Daskalakis, Christos H. Papadimitriou
MICCAI
2007
Springer
14 years 8 months ago
Object Localization Based on Markov Random Fields and Symmetry Interest Points
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov...
Branislav Micusík, Georg Langs, Horst Bisch...
ECAI
2006
Springer
13 years 10 months ago
Polynomial Conditional Random Fields for Signal Processing
We describe Polynomial Conditional Random Fields for signal processing tasks. It is a hybrid model that combines the ability of Polynomial Hidden Markov models for modeling complex...
Trinh Minh Tri Do, Thierry Artières