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Proceedings Paper

Searching through photographic databases with QuickLook
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Paper Abstract

We present here the results obtained by including a new image descriptor, that we called prosemantic feature vector, within the framework of QuickLook2 image retrieval system. By coupling the prosemantic features and the relevance feedback mechanism provided by QuickLook2, the user can move in a more rapid and precise way through the feature space toward the intended goal. The prosemantic features are obtained by a two-step feature extraction process. At the first step, low level features related to image structure and color distribution are extracted from the images. At the second step, these features are used as input to a bank of classifiers, each one trained to recognize a given semantic category, to produce score vectors. We evaluated the efficacy of the prosemantic features under search tasks on a dataset provided by Fratelli Alinari Photo Archive.

Paper Details

Date Published: 9 February 2012
PDF: 10 pages
Proc. SPIE 8304, Multimedia on Mobile Devices 2012; and Multimedia Content Access: Algorithms and Systems VI, 83040V (9 February 2012); doi: 10.1117/12.911976
Show Author Affiliations
Gianluigi Ciocca, Univ. degli Studi di Milano-Bicocca (Italy)
Claudio Cusano, Univ. degli Studi di Milano-Bicocca (Italy)
Raimondo Schettini, Univ. degli Studi di Milano-Bicocca (Italy)
Simone Santini, Univ. Autónoma de Madrid (Spain)
Andrea De Polo, Alinari 24 ORE SpA (Italy)
Francesca Tavanti, Alinari 24 ORE SpA (Italy)


Published in SPIE Proceedings Vol. 8304:
Multimedia on Mobile Devices 2012; and Multimedia Content Access: Algorithms and Systems VI
Cees G. M. Snoek; Reiner Creutzburg; Nicu Sebe; David Akopian; Lyndon Kennedy, Editor(s)

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