Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
A new class of kernels for object recognition based on local image feature representations are introduced in this paper. These kernels satisfy the Mercer condition and incorporate...
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
There have been important recent advances in object recognition through the matching of invariant local image features. However, the existing approaches are based on matching to i...