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Bayesian Probabilistic Models for Image Retrieval
Published on Nov 11, 20113368 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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Chapter list
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