We propose a new self-adaptive image cropping algorithm where the processing steps are driven by the classification of the images into semantic classes. The algorithm exploits both visual and semantic information. Visual information is obtained from a visual attention model, while semantic information relates to the automatically assigned image genre and to the detection of face and skin regions.
Schettini, R., Gasparini, F., Cusano, C., Ciocca, G. (2007). Self-Adaptive Image Cropping for Small Displays. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 53(4), 1622-1627 [10.1109/TCE.2007.4429261].
Self-Adaptive Image Cropping for Small Displays
SCHETTINI, RAIMONDO;GASPARINI, FRANCESCA;CUSANO, CLAUDIO;CIOCCA, GIANLUIGI
2007
Abstract
We propose a new self-adaptive image cropping algorithm where the processing steps are driven by the classification of the images into semantic classes. The algorithm exploits both visual and semantic information. Visual information is obtained from a visual attention model, while semantic information relates to the automatically assigned image genre and to the detection of face and skin regions.
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