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» On Weak Markov's Principle
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CVIU
2006
76views more  CVIU 2006»
13 years 7 months ago
Homeostatic image perception: An artificial system
This paper describes how a visual system can automatically define features of interest from the observation of a large enough number of natural images. The principle complements t...
Thomas Feldman, Laurent Younes
QEST
2010
IEEE
13 years 5 months ago
Transient Analysis of Generalised Semi-Markov Processes Using Transient Stochastic State Classes
The method of stochastic state classes approaches the analysis of Generalised Semi Markov Processes (GSMP) through symbolic derivation of probability density functions over Differe...
András Horváth, Lorenzo Ridi, Enrico...
CVIU
2006
162views more  CVIU 2006»
13 years 7 months ago
Unsupervised scene analysis: A hidden Markov model approach
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...
Manuele Bicego, Marco Cristani, Vittorio Murino
ECCV
2006
Springer
14 years 9 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
ICML
2006
IEEE
14 years 8 months ago
Online decoding of Markov models under latency constraints
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...
Mukund Narasimhan, Paul A. Viola, Michael Shilman