Semi-automatic feature-adaptive relevance feedback (SA-FR-RF) for content-based image retrieval

Authors:
Anelia Grigorova;Francesco G. B. De Natale
Affiliations:
Dept. of Information and Communication Technology, University of Trento, Italy;Dept. of Information and Communication Technology, University of Trento, Italy
Venue:
VISUAL'05 Proceedings of the 8th international conference on Visual Information and Information Systems
Year:
2005

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Abstract

The paper proposes an adaptive retrieval approach based on the concept of relevance-feedback, which establishes a link between high-level concepts and low-level features. The user’s feedback is used not only to assign proper weights to the features, but also to dynamically select them and to identify the set of relevant features according to a user query, maintaining at the same time a small sized feature vector to attain better matching and lower complexity. Results achieved on a large image dataset show that the proposed algorithm outperforms previously proposed methods. Further, it is experimentally demonstrated that it approaches the results obtained by optimum feature selection techniques having complete knowledge of the data set.