Abstract: An approach to recognize scene categories by means of a novel model named bag of spatial visual words was proposed. Images were hierarchically divided into sub regions and the spatial visual vocabulary was constructed by grouping the low-level features collected from every corresponding spatial sub region into a specified number of clusters using k-means algorithm. To recognize the category of a scene, the visual vocabulary distributions of all spatial sub regions were concatenated to form a global feature vector.The classification result was obtained using LIBSVM and two kinds of features were used in the experiments:"V1-like" filters and PACK features.

Key words: Scene classification,Bag of words, Spatial clustering, Spatial visual vocabulary, SVM