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Bayesian Probabilistic Models for Image Retrieval
Published on 2011-11-113377 Views
In this paper we present new probabilistic ranking functions for content based image retrieval. Our methodology generalises previous approaches and is based on the predictive densities of generative p
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Presentation
Bayesian Probabilistic Models for Image Retrieval00:00
Outline00:52
Bag of Terms Image Retrieval01:35
Region Detection02:55
Feature Description05:51
Code-block Generation & Quantisation08:20
Probabilistic IR Models11:14
Language Models for IR - 112:08
Language Models for IR - 215:34
Probabilistic Models for Image Retrieval17:14
Model Predictive Density19:20
Multinomial-Dirichlet Model21:07
Gaussian Mixture Model22:13
Variational Inference for Gaussian Mixture Model - 123:49
Variational Inference for Gaussian Mixture Model - 227:28
Variational Inference for Gaussian Mixture Model - 330:38
Determining the Number of Components32:54
Corel 5K Test Collection34:44
Pre-processing35:38
Results - 137:51
Results - 241:43
Conclusions43:45
Future Work45:32
References - 148:44
References - 248:47