Image pattern discovery by using the spatial closeness of visual code words
Meng Sun, Hugo Van hamme · 2011
A graph regularized non-negative matrix factorization (NMF) model is proposed for image pattern discovery. Each image is represented by its histogram of visual words (i.e. bag-of-words) and the image contents are discovered by the NMF model. The graph regularization preserves the spatial closeness of visual code words in the obtained patterns, thus improving the bag-of-words representation against its main shortcoming: the loss of spatial information. Experiments on a subset of the Caltech256 database show the efficacy of the proposed model.