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» Mixture model based contextual image retrieval
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ICCV
2005
IEEE
15 years 4 months ago
Bayesian Body Localization Using Mixture of Nonlinear Shape Models
We present a 2D model-based approach to localizing human body in images viewed from arbitrary and unknown angles. The central component is a statistical shape representation of th...
Jiayong Zhang, Robert T. Collins, Yanxi Liu
IJCV
2006
116views more  IJCV 2006»
14 years 11 months ago
Contextual Inference in Contour-Based Stereo Correspondence
Standard approaches to stereo correspondence have difficulty when scene structure does not lie in or near the frontal parallel plane, in part because an orientation disparity as we...
Gang Li, Steven W. Zucker
CAIP
2009
Springer
211views Image Analysis» more  CAIP 2009»
15 years 5 months ago
Contextual-Guided Bag-of-Visual-Words Model for Multi-class Object Categorization
Abstract. Bag-of-words model (BOW) is inspired by the text classification problem, where a document is represented by an unsorted set of contained words. Analogously, in the objec...
Mehdi Mirza-Mohammadi, Sergio Escalera, Petia Rade...
SAC
2005
ACM
15 years 4 months ago
A hierarchical naive Bayes mixture model for name disambiguation in author citations
Because of name variations, an author may have multiple names and multiple authors may share the same name. Such name ambiguity affects the performance of document retrieval, web ...
Hui Han, Wei Xu, Hongyuan Zha, C. Lee Giles
CORR
2010
Springer
171views Education» more  CORR 2010»
14 years 11 months ago
Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
Guoshen Yu, Guillermo Sapiro, Stéphane Mall...