Effective keyword search on image databases is a major open problem, due to the inherent imprecision of keywords (tags) used to describe images' content. In this paper we present a novel approach to deal with this problem, as implemented in the Scenique image retrieval and browsing system. Scenique is based on a multi-dimensional model, where each dimension is a tree-structured taxonomy of concepts, also called semantic tags, that are used to describe the content of images. We first describe an original algorithm, called Ostia (Optimal Semantic Tags for Image Annotation), that, by exploiting low-level visual features, tags, and metadata associated to an image, is able to predict a high-quality set of semantic tags for that image. Then, we describe how semantic tags can be effectively used for the purpose of improving the precision of keyword search.

Multi-dimensional Keyword-based Image Annotation and Search

BARTOLINI, ILARIA;CIACCIA, PAOLO
2010

Abstract

Effective keyword search on image databases is a major open problem, due to the inherent imprecision of keywords (tags) used to describe images' content. In this paper we present a novel approach to deal with this problem, as implemented in the Scenique image retrieval and browsing system. Scenique is based on a multi-dimensional model, where each dimension is a tree-structured taxonomy of concepts, also called semantic tags, that are used to describe the content of images. We first describe an original algorithm, called Ostia (Optimal Semantic Tags for Image Annotation), that, by exploiting low-level visual features, tags, and metadata associated to an image, is able to predict a high-quality set of semantic tags for that image. Then, we describe how semantic tags can be effectively used for the purpose of improving the precision of keyword search.
Proceedings of the 2nd International Workshop on Keyword Search on Structured Data (KEYS 2010)
5-1
5-6
I. Bartolini; P. Ciaccia
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/93486
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