Abstract
The visual vocabularyis 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, in- dependently of the object model used for categorizing images. We propose here to embed the visual vocabulary creation within the object model con- struction, 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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