Proceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015
Doi
Abstract
Object instance recognition approaches based on the
bag-of-words model are severely affected by the loss of
spatial consistency during retrieval. As a result, costly
RANSAC verification is needed to ensure geometric
consistency between the query and the retrieved images.
A common alternative is to inject geometric informa-
tion directly into the retrieval procedure, by endowing
the visual words with additional information. Most of
the existing approaches in this category can efficiently
handle only restricted classes of geometric transfor-
mations, including scale and translation. In this pa-
per, we propose a simple and efficient scheme that can
cover the more complex class of full affine transforma-
tions. We demonstrate the usefulness of our approach
in the case of planar object instance recognition, such
as recognition of books, logos, traffic signs, etc.This work was funded by a Google Faculty Research
Award, the Marie Curie grant CIG-334283-HRGP, a
CNRS chaire d'excellence.This is the author accepted manuscript. The final version is available at http://dx.doi.org/10.1109/MVA.2015.715312
