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ICMCS
2009
IEEE
415views Multimedia» more  ICMCS 2009»
13 years 5 months ago
A new localized superpixel Markov random field for image segmentation
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
Xiaofeng Wang, Xiao-Ping Zhang
NIPS
2008
13 years 8 months ago
Multiscale Random Fields with Application to Contour Grouping
We introduce a new interpretation of multiscale random fields (MSRFs) that admits efficient optimization in the framework of regular (single level) random fields (RFs). It is base...
Longin Jan Latecki, ChengEn Lu, Marc Sobel, Xiang ...
CVPR
2007
IEEE
14 years 9 months ago
Utilizing Variational Optimization to Learn Markov Random Fields
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
Marshall F. Tappen
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 2 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
ACCV
1998
Springer
13 years 11 months ago
Motion Compensated Color Video Classification Using Markov Random Fields
Abstract. This paper deals with the classification of color video sequences using Markov Random Fields (MRF) taking into account motion information. The theoretical framework relie...
Zoltan Kato, Ting-Chuen Pong, John Chung-Mong Lee