We propose a novel lightweight method for classifying scene images, which fits well on weak machines, mobiles, or embedded devices. Our feature representation technique, which we call SOGI or Spatial Oriented Gradient Indexing, requires a small amount both of computational time and space. We show that, by capturing the spatial co-occurrence of gradient pairs, we provide sufficient amount of information for scene classification task. Despise the simplicity, experimental result shows that our method can still be comparable to other complicated methods on their own datasets.
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