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» Global Ranking Using Continuous Conditional Random Fields
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SIAMIS
2010
378views more  SIAMIS 2010»
13 years 29 days 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
PREMI
2009
Springer
14 years 23 days ago
Unsupervised Color Image Segmentation Using Compound Markov Random Field Model
Abstract. In this paper, we propose an unsupervised color image segmentation scheme using homotopy continuation method and Compound Markov Random Field (CMRF) model. The proposed s...
Sucheta Panda, P. K. Nanda
SIAMCO
2011
13 years 1 months ago
Consistency of Sequential Bayesian Sampling Policies
We consider Bayesian information collection, in which a measurement policy collects information to support a future decision. This framework includes ranking and selection, continu...
Peter Frazier, Warren B. Powell
CVPR
2008
IEEE
13 years 8 months ago
A rank constrained continuous formulation of multi-frame multi-target tracking problem
This paper presents a multi-frame data association algorithm for tracking multiple targets in video sequences. Multi-frame data association involves finding the most probable corr...
Khurram Shafique, Mun Wai Lee, Niels Haering
ECCV
2008
Springer
14 years 8 months ago
Latent Pose Estimator for Continuous Action Recognition
Recently, models based on conditional random fields (CRF) have produced promising results on labeling sequential data in several scientific fields. However, in the vision task of c...
Huazhong Ning, Wei Xu, Yihong Gong, Thomas S. Huan...