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PAMI
2007
196views more  PAMI 2007»
13 years 7 months ago
Clustering and Embedding Using Commute Times
This paper exploits the properties of the commute time between nodes of a graph for the purposes of clustering and embedding, and explores its applications to image segmentation a...
Huaijun Qiu, Edwin R. Hancock
ECCV
2006
Springer
14 years 9 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields
One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with som...
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
CVPR
2010
IEEE
14 years 1 months ago
Semantic Context Modeling with Maximal Margin Conditional Random Fields for Automatic Image Annotation
Context modeling for Vision Recognition and Automatic Image Annotation (AIA) has attracted increasing attentions in recent years. For various contextual information and resources,...
Yu Xiang, Xiangdong Zhou, Zuotao Liu, Tat-seng chu...
SODA
1997
ACM
169views Algorithms» more  SODA 1997»
13 years 8 months ago
Partial Matching of Planar Polylines Under Similarity Transformations
Given two planar polylines T and P with n and m edges, respectively, we present an Om2 n2  time, Omn space algorithm to nd portions of the text" T which are similar in sh...
Scott D. Cohen, Leonidas J. Guibas
ECCV
2002
Springer
14 years 9 months ago
Stereo Matching Using Belief Propagation
In this paper, we formulate the stereo matching problem as a Markov network consisting of three coupled Markov random fields (MRF's). These three MRF's model a smooth fie...
Jian Sun, Heung-Yeung Shum, Nanning Zheng