We present here, an image description approach based on prosemantic features. The images are represented by a set of low-level features related to their structure and color distribution. Those descriptions are fed to a battery of image classifiers trained to evaluate the membership of the images with respect to a set of 14 overlapping classes. Prosemantic features are obtained by packing together the scores. To verify the effectiveness of the approach, we designed a target search experiment in which both low-level and prosemantic features are embedded into a content-based image retrieval system exploiting relevance feedback. The experiments show that the use of prosemantic features allows for a more successful and quick retrieval of the query images. © 2011 Springer-Verlag Berlin Heidelberg.

Ciocca, G., Cusano, C., Santini, S., Schettini, R. (2011). Prosemantic features for content-based image retrieval. In Adaptive Multimedia Retrieval. Understanding Media and Adapting to the User (pp.87-100). Heidelberg : Springer [10.1007/978-3-642-18449-9_8].

Prosemantic features for content-based image retrieval

CIOCCA, GIANLUIGI;CUSANO, CLAUDIO;SCHETTINI, RAIMONDO
2011

Abstract

We present here, an image description approach based on prosemantic features. The images are represented by a set of low-level features related to their structure and color distribution. Those descriptions are fed to a battery of image classifiers trained to evaluate the membership of the images with respect to a set of 14 overlapping classes. Prosemantic features are obtained by packing together the scores. To verify the effectiveness of the approach, we designed a target search experiment in which both low-level and prosemantic features are embedded into a content-based image retrieval system exploiting relevance feedback. The experiments show that the use of prosemantic features allows for a more successful and quick retrieval of the query images. © 2011 Springer-Verlag Berlin Heidelberg.
Si
slide + paper
prosemantic features, content based image retrieval, image indexing, classification, image annotation
English
7th International Workshop on Adaptive Multimedia Retrieval
978-3-642-18448-2
2011
Ciocca, G., Cusano, C., Santini, S., Schettini, R. (2011). Prosemantic features for content-based image retrieval. In Adaptive Multimedia Retrieval. Understanding Media and Adapting to the User (pp.87-100). Heidelberg : Springer [10.1007/978-3-642-18449-9_8].
Ciocca, G; Cusano, C; Santini, S; Schettini, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/16572
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