Geometric Latent Dirichlet Allocation on a matching graph for large-scale image datasets

<p>Given a large-scale collection of images our aim is to efficiently associate images which contain the same entity, for example a building or object, and to discover the significant entities. To achieve this, we introduce the Geometric Latent Dirichlet Allocation (gLDA) model for unsupervise...

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Bibliographic Details
Main Authors: Philbin, J, Sivic, J, Zisserman, A
Format: Journal article
Language:English
Published: Springer 2011
Subjects: