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» Markov Random Field Modeling in Computer Vision
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ICPR
2008
IEEE
14 years 3 months ago
A Mixed Markov model for change detection in aerial photos with large time differences
In the paper we propose a novel multi-layer Mixed Markov model for detecting relevant changes in registered aerial images taken with significant time differences. The introduced ...
Csaba Benedek, Tamás Szirányi
AAAI
2008
13 years 11 months ago
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver
Conditional random field (CRF) is a popular graphical model for sequence labeling. The flexibility of CRF poses significant computational challenges for training. Using existing o...
Minmin Chen, Yixin Chen, Michael R. Brent
ICPR
2006
IEEE
14 years 10 months ago
Hidden Markov Models for Optical Flow Analysis in Crowds
This paper presents an event detector for emergencies in crowds. Assuming a single camera and a dense crowd we rely on optical flow instead of tracking statistics as a feature to ...
Ernesto L. Andrade, Scott Blunsden, Robert B. Fish...
ICPR
2010
IEEE
13 years 7 months ago
Visual Recognition of Types of Structural Corridor Landmarks Using Vanishing Points Detection and Hidden Markov Models
In this paper, to provide a robot with information relative to structure of its environment, we propose a method to recognize types of structural corridor landmarks such as T-junct...
Youngbin Park, Sung Su Kim, Il Hong Suh
ICPR
2004
IEEE
14 years 10 months ago
To FRAME or not to FRAME in Probabilistic Texture Modelling?
The maximum entropy principle is a cornerstone of FRAME (Filters, RAndom fields, and Maximum Entropy) model considered at times as a first-ever step towards a universal theory of ...
Georgy L. Gimel'farb, Luc J. Van Gool, Alexey Zale...