S-IRAS: An Interactive Semantic Image Retrieval and Annotation System

Changbo Yang, Ming Dong and Farshad Fotouhi
Additional contact information
Changbo Yang: Wayne State University, USA
Ming Dong: Wayne State University, USA
Farshad Fotouhi: Wayne State University, USA

International Journal on Semantic Web and Information Systems (IJSWIS), 2006, vol. 2, issue 3, 37-54

Abstract: Relevance feedback and semantic retrieval have received extensive attention recently in the computer vision community. In this article, we present a semantic image query system with integrated feedback mechanism. Our system has two major components: the low-level feature space and the semantic space. In the low-level feature space, images are described by multidimensional vectors and are clustered based on the similarity of their contents. In the semantic space, the relationship among keywords is captured by a semantic hierarchy built by the aid of WordNet. Based on our system architecture, we propose a novel feedback solution for semantic retrieval called semantic feedback, which allows our system to interact with users directly at the semantic level. The short-term and long-term learning process of the semantic feedback substantially improves the image retrieval and annotation performance of our system. We demonstrate the effectiveness of our approach with experiments using 5,000 images from Corel database. The significant contribution of this article is in the scenario of having a relatively small training data set compared to the testing data set. Some of the previous work in the same direction has chosen a very large training set and a very small testing set. Clearly, the problem that we try to solve is more realistic and challenging.

Date: 2006
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/jswis.2006070103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jswis0:v:2:y:2006:i:3:p:37-54

Access Statistics for this article

International Journal on Semantic Web and Information Systems (IJSWIS) is currently edited by Brij Gupta

More articles in International Journal on Semantic Web and Information Systems (IJSWIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().