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» Markov Random Field Modeling in Computer Vision
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ECCV
2002
Springer
14 years 11 months ago
Hyperdynamics Importance Sampling
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...
Cristian Sminchisescu, Bill Triggs
ICPR
2002
IEEE
14 years 10 months ago
Fractional Component Analysis (FCA) for Mixed Signals
This paper proposes the fractional component analysis (FCA), whose goal is to decompose the observed signal into component signals and recover their fractions. The uniqueness of o...
Asanobu Kitamoto
CVPR
2008
IEEE
14 years 11 months ago
Interactive image segmentation via minimization of quadratic energies on directed graphs
We propose a scheme to introduce directionality in the Random Walker algorithm for image segmentation. In particular, we extend the optimization framework of this algorithm to com...
Dheeraj Singaraju, Leo Grady, René Vidal
CVPR
2004
IEEE
14 years 11 months ago
Motion Estimation by Swendsen-Wang Cuts
Our paper has two main contributions. Firstly, it presents a model for image sequences motivated by an image encoding perspective. It models accreted regions, where objects appear...
Adrian Barbu, Alan L. Yuille
BMCBI
2010
123views more  BMCBI 2010»
13 years 9 months ago
Decoding HMMs using the k best paths: algorithms and applications
Background: Traditional algorithms for hidden Markov model decoding seek to maximize either the probability of a state path or the number of positions of a sequence assigned to th...
Daniel G. Brown 0001, Daniil Golod