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We investigate the utility of human performance data on indoor-outdoor scene categorization in improving the generalization performance of a machine indoor-outdoor classifier. On 50 indoor and 50 outdoor scenes, the human categorization accuracies are obtained for these stimuli rendered as either real images or line drawings. We study two types of features, image gist and edge gist, which are the...
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