A new spatial weighting scheme for bag-of-visual-words

In this paper, we develop a novel image representation method which is based firstly on constructing visual words based on a local patch extraction and a fusion of descriptors. The spatial constitution of an image is represented with a mixture of n Gaussians in the feature space. The new spatial weighting scheme consists in weighting visual words according to the probability of each visual word belongs to each of the n Gaussians. Experimental results show that the proposed approach integrated to an image retrieval system, outperforms the results of traditional image retrieval techniques.