Semantic spaces revisited: investigating the performance of auto-annotation and semantic retrieval using semantic spaces

Authors:
Jonathon S. Hare;Sina Samangooei;Paul H. Lewis;Mark S. Nixon
Affiliations:
University of Southampton, Southampton, United Kngdm;University of Southampton, Southampton, United Kngdm;University of Southampton, Southampton, United Kngdm;University of Southampton, Southampton, United Kngdm
Venue:
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Year:
2008

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Abstract

Semantic spaces encode similarity relationships between objects as a function of position in a mathematical space. This paper discusses three different formulations for building semantic spaces which allow the automatic-annotation and semantic retrieval of images. The models discussed in this paper require that the image content be described in the form of a series of visual-terms, rather than as a continuous feature-vector. The paper also discusses how these term-based models compare to the latest state-of-the-art continuous feature models for auto-annotation and retrieval.