Mind the Gap: Another look at the problem of the semantic gap in image retrieval

This paper attempts to review and characterise the problem of the semantic gap in image retrieval and the attempts being made to bridge it. In particular, we draw from our own experience in user queries, automatic annotation and ontological techniques. The first section of the paper describes a characterisation of the semantic gap as a hierarchy between the raw media and full semantic understanding of the media's content. The second section discusses real users' queries with respect to the semantic gap. The final sections of the paper describe our own experience in attempting to bridge the semantic gap. In particular we discuss our work on auto-annotation and semantic-space models of image retrieval in order to bridge the gap from the bottom up, and the use of ontologies, which capture more semantics than keyword object labels alone, as a technique for bridging the gap from the top down

Semantic Facets: An in-depth Analysis of a Semantic Image Retrieval System

This paper introduces a faceted model of image semantics which attempts to express the richness of semantic content interpretable within an image. Using a large image data-set from a museum collection the paper shows how the facet representation can be applied. The second half of the paper describes our semantic retrieval system, and demonstrates its use with the museum image collection. A retrieval evaluation is performed using the system to investigate how the retrieval performance varies with respect to each of the facet categories. A number of factors related to the image data-set that affect the quality of retrieval are also discussed

How to spot a Dalmatian in a pack of Dogs; A data-driven approach to searching unannotated images using natural language

This poster demonstrates our recent work in the field of intelligent image retrieval in response to real requests from the practitioner domain. The poster shows how we are developing a data-driven 'semantic space' framework for information retrieval which can enable retrieval of unannotated imagery through natural language queries, and also facilitate automatic annotation of imagery

The Reality of the Semantic Gap in Image Retrieval

The semantic gap is referred to frequently in papers on image retrieval or multimedia information handling. However, whilst many authors have been happy to make reference to it, few have attempted to characterize the gap in any detail. This tutorial will attempt to rectify this situation by characterizing the semantic gap in image retrieval rather more specifically than hitherto. It will summarise current attempts to begin to bridge the gap both through developments in content-based techniques, the application of semantic web and knowledge technologies and recent progress in auto image annotation. The tutorial will consist of presentations/demonstrations partly based on research in recent European and UK projects, and particularly on a project to investigate the semantic gap funded by the Arts and Humanities Research Council in the UK involving the four presenters. This tutorial aims to provide valuable insights for those involved in research and development on image or multimedia retrieval and who wish to understand and address the concerns of real end-users and exploit recent research results in the field. In particular, the tutorial will provide practical insights into the problems associated with bridging the communication gap between the computer science/vision research community and the image management/practitioner community. The first presentation will summarise research into the way picture searchers articulate real queries, how the

Facing the reality of semantic image retrieval

Purpose – To provide a better-informed view of the extent of the semantic gap in image retrieval, and the limited potential for bridging it offered by current semantic image retrieval techniques. Design/methodology/approach – Within an ongoing project, a broad spectrum of operational image retrieval activity has been surveyed, and, from a number of collaborating institutions, a test collection assembled which comprises user requests, the images selected in response to those requests, and their associated metadata. This has provided the evidence base upon which to make informed observations on the efficacy of cutting-edge automatic annotation techniques which seek to integrate the text-based and content-based image retrieval paradigms. Findings – Evidence from the real-world practice of image retrieval highlights the existence of a generic-specific continuum of object identification, and the incidence of temporal, spatial, significance and abstract concept facets, manifest in textual indexing and real-query scenarios but often having no directly visible presence in an image. These factors combine to limit the functionality of current semantic image retrieval techniques, which interpret only visible features at the generic extremity of the generic-specific continuum. Research limitations/implications – The project is concerned with the traditional image retrieval environment in which retrieval transactions are conducted on still images which form part of managed collections. The possibilities offered by ontological support for adding functionality to automatic annotation techniques are considered. Originality/value – The paper offers fresh insights into the challenge of migrating content-based image retrieval from the laboratory to the operational environment, informed by newly-assembled, comprehensive, live data

Tuning the Magnetic Properties of Metal Oxide Nanocrystal Heterostructures by Cation Exchange

For three types of colloidal magnetic nanocrystals, we demonstrate that postsynthetic cation exchange enables tuning of the nanocrystal’s magnetic properties and achieving characteristics not obtainable by conventional synthetic routes. While the cation exchange procedure, performed in solution phase approach, was restricted so far to chalcogenide based semiconductor nanocrystals, here ferrite-based nanocrystals were subjected to a Fe2+ to Co2+ cation exchange procedure. This allows tracing of the compositional modifications by systematic and detailed magnetic characterization. In homogeneous magnetite nanocrystals and in gold/magnetite core shell nanocrystals the cation exchange increases the coercivity field, the remanence magnetization, as well as the superparamagnetic blocking temperature. For core/shell nanoheterostructures a selective doping of either the shell or predominantly of the core with Co2+ is demonstrated. By applying the cation exchange to FeO/CoFe2O4 core/shell nanocrystals the Neél temperature of the core material is increased and exchange-bias effects are enhanced so that vertical shifts of the hysteresis loops are obtained which are superior to those in any other system