Building global image features for scene recognition
Pattern Recognition
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An approach for rapid scene perception from global layout to local features is presented. The representation of a complex scene is initially built from a collection of global features from which properties related to the spatial layout of the scene and its semantic category can be estimated. The rapid perception of natural scenes relies partly on a global estimation of the features contained in the scene. Further analysis on the local essential areas is deployed on the basis. Such kind of integrated model guarantees the interactive processing between local and global features, thus enabling low-level features to initiate scene perception and categorization efficiently.