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17 years 1 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
CVPR
2010
IEEE
1790views Computer Vision» more  CVPR 2010»
15 years 11 months ago
Data Driven Mean-Shift Belief Propagation For non-Gaussian MRFs
We introduce a novel data-driven mean-shift belief propagation (DDMSBP) method for non-Gaussian MRFs, which often arise in computer vision applications. With the aid of scale sp...
Minwoo Park, S. Kashyap, R. Collins, and Y. Liu
PODS
2010
ACM
159views Database» more  PODS 2010»
15 years 4 months ago
On probabilistic fixpoint and Markov chain query languages
We study highly expressive query languages such as datalog, fixpoint, and while-languages on probabilistic databases. We generalize these languages such that computation steps (e....
Daniel Deutch, Christoph Koch, Tova Milo
PODC
2010
ACM
15 years 6 months ago
Adaptive randomized mutual exclusion in sub-logarithmic expected time
Mutual exclusion is a fundamental distributed coordination problem. Shared-memory mutual exclusion research focuses on local-spin algorithms and uses the remote memory references ...
Danny Hendler, Philipp Woelfel
COMPGEOM
2003
ACM
15 years 8 months ago
Morse-smale complexes for piecewise linear 3-manifolds
We define the Morse-Smale complex of a Morse function over a 3-manifold as the overlay of the descending and ascending manifolds of all critical points. In the generic case, its ...
Herbert Edelsbrunner, John Harer, Vijay Natarajan,...