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ECCV
2008
Springer
14 years 11 months ago
A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus
The Random Sample Consensus (RANSAC) algorithm is a popular tool for robust estimation problems in computer vision, primarily due to its ability to tolerate a tremendous fraction o...
Rahul Raguram, Jan-Michael Frahm, Marc Pollefeys
ICPR
2010
IEEE
14 years 4 months ago
Continuous Markov Random Field Optimization using Fusion Move Driven Markov Chain Monte Carlo Technique
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
COMPGEOM
1998
ACM
14 years 1 months ago
Geometric Applications of a Randomized Optimization Technique
Abstract. We propose a simple, general, randomized technique to reduce certain geometric optimization problems to their corresponding decision problems. These reductions increase t...
Timothy M. Chan
BMCBI
2007
89views more  BMCBI 2007»
13 years 9 months ago
Comparing segmentations by applying randomization techniques
Background: There exist many segmentation techniques for genomic sequences, and the segmentations can also be based on many different biological features. We show how to evaluate ...
Niina Haiminen, Heikki Mannila, Evimaria Terzi
ICCV
2007
IEEE
14 years 11 months ago
LogCut - Efficient Graph Cut Optimization for Markov Random Fields
Markov Random Fields (MRFs) are ubiquitous in lowlevel computer vision. In this paper, we propose a new approach to the optimization of multi-labeled MRFs. Similarly to -expansion...
Victor S. Lempitsky, Carsten Rother, Andrew Blake