Annotating photographs with broad semantic labels can be useful in both image processing and content-based image retrieval. We show here how low-level features can be related to semantic photo categories, such as indoor, outdoor and close-up, using decision forests consisting of trees constructed according to CART methodology. We also show how the results can be improved by introducing a rejection option in the classification process. Experimental results on a test set of 4,500 photographs are reported and discussed.
Schettini, R., Cusano, C., Ciocca, G., Brambilla, C. (2004). Automatic classification of digital photographs based on decision forests. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 18(5), 819-845 [10.1142/S0218001404003435].
Automatic classification of digital photographs based on decision forests
SCHETTINI, RAIMONDO;CUSANO, CLAUDIO;CIOCCA, GIANLUIGI;
2004
Abstract
Annotating photographs with broad semantic labels can be useful in both image processing and content-based image retrieval. We show here how low-level features can be related to semantic photo categories, such as indoor, outdoor and close-up, using decision forests consisting of trees constructed according to CART methodology. We also show how the results can be improved by introducing a rejection option in the classification process. Experimental results on a test set of 4,500 photographs are reported and discussed.
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