High discriminative SIFT feature and feature pair selection to improve the bag of visual words model.

The bag of visual words (BOW) model has been widely applied in the field of image recognition and image classification. However, all scale-invariant feature transform (SIFT) features are clustered to construct the visual words which result in a substantial loss of discriminative power for the visual words. The corresponding visual phrases will further render the generated BOW histogram sparse. In ...