Dynamic queries with relevance feedback for content based image retrieval

Authors:
Murat Birinci;Esin Guldogan;Moncef Gabbouj
Affiliations:
Department of Signal Processing, Tampere University of Technology, Tampere, Finland;Department of Signal Processing, Tampere University of Technology, Tampere, Finland;Department of Signal Processing, Tampere University of Technology, Tampere, Finland
Venue:
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: design and development approaches - Volume Part I
Year:
2011

Citing 5
Cited 0

Dynamic Queries for Visual Information Seeking

IEEE Software
Direct Manipulation: A Step Beyond Programming Languages

Computer
Two Step Relevance Feedback for Semantic Disambiguation in Image Retrieval

VISUAL '08 Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management
Fuzzy SVM ensembles for relevance feedback in image retrieval

CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
An Object- and User-Driven System for Semantic-Based Image Annotation and Retrieval

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

A novel relevance feedback scheme utilizing dynamic queries for content based image retrieval systems is proposed, where the retrieval results are updated instantly based on the user's feedback. The user is expected to label at least one image as positive or negative, revealing the gist of the expected retrieval results. Then the retrieval results are updated dynamically, without any further user interaction, based on the similarity of the query and the selected image in different feature spaces increasing the semantic accuracy of the retrieval. The proposed method not only invalidates the drawbacks of current relevance feedback systems in terms of user experience, but also provides an innovative stand point for the relevance feedback scheme as well.