Client-side content-based refinement for image search in the web

Authors:
F. N. Bezerra;E. Werbet;W. B. Silva
Affiliations:
Universidade de Fortaleza;Universidade de Fortaleza;Universidade de Fortaleza
Venue:
WebMedia '05 Proceedings of the 11th Brazilian Symposium on Multimedia and the web
Year:
2005

Citing 5
Cited 2

Visual information retrieval

Visual information retrieval
The Holy Grail of Content-Based Media Analysis

IEEE MultiMedia
A 20th Anniversary Survey: Introduction to 'Content-Based Image Retrieval at the End of the Early Years'

IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Retrieval from the World Wide Web: Issues, Techniques, and Systems

ACM Computing Surveys (CSUR)
Color and texture descriptors

IEEE Transactions on Circuits and Systems for Video Technology

Client-Side Relevance Feedback Approach for Image Retrieval in Mobile Environment

International Journal of Multimedia Data Engineering & Management
Towards improving the online shopping experience: A client-based platform for post-processing Web search results

Web Intelligence and Agent Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Image queries in web search engines is restricted to queries by keyword, i.e. queries by visual content are not yet available in current engines. A main difficulty in the development of such queries is the absence of precomputed low level image descriptors for the huge image content in the web. We present a pseudo relevance feedback approach to allow the addition of query refinements by visual content. The user feedback is processed at client side to improve the search result based on image colors.