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» Unsupervised scene analysis: A hidden Markov model approach
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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
14 years 5 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
ICCV
2009
IEEE
13 years 5 months ago
Analysis of orientation and scale in smoothly varying textures
We present a novel representation for modeling textured regions subject to smooth variations in orientation and scale. Utilizing the steerable pyramid of Simoncelli and Freeman as...
Jason Chang, John W. Fisher III
CVPR
2011
IEEE
13 years 3 months ago
Random Field Topic Model for Semantic Region Analysis in Crowded Scenes from Tracklets
In this paper, a Random Field Topic (RFT) model is proposed for semantic region analysis from motions of objects in crowded scenes. Different from existing approaches of learning ...
Bolei Zhou, Xiaogang Wang
BMCBI
2008
103views more  BMCBI 2008»
13 years 7 months ago
Parameter estimation for robust HMM analysis of ChIP-chip data
Background: Tiling arrays are an important tool for the study of transcriptional activity, proteinDNA interactions and chromatin structure on a genome-wide scale at high resolutio...
Peter Humburg, David Bulger, Glenn Stone
ICCV
2007
IEEE
14 years 9 months ago
Scene Modeling Using Co-Clustering
In this paper, we propose a novel approach for scene modeling. The proposed method is able to automatically discover the intermediate semantic concepts. We utilize Maximization of...
Jingen Liu, Mubarak Shah