Mean BoF per quadrant: Simple and effective way to embed spatial information in bag of features

This paper proposes a new approach for embedding spatial information into a Bag of Features image descriptor, primarily meant for image retrieval. The method is conceptually related to Spatial Pyramids but instead of requiring fixed and arbitrary sub-regions where to compute region-based BoF, it relies on an adaptive procedure based on multiple partitioning of the image in four quadrants (the NE, NW, SE, SW regions of the image). To obtain a compact and efficient description, all BoF related to the same quadrant are averaged, obtaining four descriptors which capture the dominant structures of the main areas of the image, and then concatenated. The computational cost of the method is the same as BoF and the size of the descriptor comparable to BoF, but the amount of spatial information retained is considerable, as shown in the experimental analysis carried out on benchmarks.