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ICIP
2005
IEEE
16 years 2 months ago
A segmentation method using compound Markov random fields based on a general boundary model
Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...
Jue Wu, Albert C. S. Chung
ICIP
2005
IEEE
16 years 2 months ago
Parameter estimation of multi-dimensional hidden Markov models - a scalable approach
Parameter estimation is a key computational issue in all statistical image modeling techniques. In this paper, we explore a computationally efficient parameter estimation algorith...
Dhiraj Joshi, Jia Li, James Ze Wang
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ICIP
2004
IEEE
16 years 2 months ago
Stochastic modeling of volume images with a 3-d hidden markov model
Over the years, researchers in the image analysis community have successfully used various statistical modeling methods to segment, classify, and annotate digital images. In this ...
Jia Li, Dhiraj Joshi, James Ze Wang
ICASSP
2009
IEEE
15 years 7 months ago
Map approach to learning sparse Gaussian Markov networks
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
Narges Bani Asadi, Irina Rish, Katya Scheinberg, D...
ICIP
2005
IEEE
15 years 6 months ago
Robust highlight extraction using multi-stream hidden Markov models for baseball video
This paper proposes a robust statistical framework to extract highlights from a baseball broadcast video. We applied multistream Hidden Markov Models (HMMs) to control the weights...
Nguyen Huu Bach, Koichi Shinoda, Sadaoki Furui