PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Latent Mixture Vocabularies for Object Categorization
Diane Larlus and Frederic Jurie
In: BMVC 2006(2006).

Abstract

The visual vocabulary is an intermediate level representation which has been proven to be very powerful for addressing object categorization problems. It is generally built by vector quantizing a set of local image descriptors, independently of the object model used for categorizing images. We propose here to embed the visual vocabulary creation within the object model construction, allowing to make it more suited for object class discrimination. We experimentally show that the proposed model outperforms approaches not learning such an adapted visual vocabulary.

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EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:2437
Deposited By:Frederic Jurie
Deposited On:22 November 2006