Prosemantic Image Retrieval

Gianluigi Ciocca¹, Claudio Cusano¹, Simone Santini², and Raimondo Schettini¹

¹Università degli Studi di Milano-Bicocca, viale Sarca 336, 20131, Milano, Italy

²Universidad Autónoma de Madrid, C/ Tomas y Valiente 11, 28049, Madrid, Spain

Abstract. In this technical demonstration we present a content-based image retrieval system based on the ‘query by example’ paradigm. The system effectiveness will be proved for both category and target search on two standard image databases, even without a “good” initial example and ancillary information, such as device metadata, text annotations, etc. These results are obtained by incorporating in the system our recently proposed prosemantic features coupled with a relevance feedback mechanism, and by maximizing novelty and diversity in the result sets.

LNCS 7585, p. 643 ff.

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