Image classification based on bag of visual graphs

This paper proposes the Bag of Visual Graphs (BoVG), a new approach to encode the spatial relationships of visual words through a codebook of visual-word arrangements, represented by graphs. This graph-based codebook defines a descriptor for image representations that not only considers the frequency of occurrence of visual words, but also their spatial relationships. Experiments demonstrate that BoVG yields high-accuracy scores in classification tasks on the traditional Caltech-101 and Caltech-256 datasets.