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Cortina: A System for Large-scale, Content-based Web Image Retrieval
T. Quack, U. Mönich, L. Thiele and B.S. Manjunath
ACM Multimedia 2004, New York, NY, USA, Oct. 2004
2004
Abstract
Recent advances in processing and networking capabilities of
computers have led to an accumulation of immense amounts
of multimedia data such as images. One of the largest repositories
for such data is the World Wide Web (WWW). We
present Cortina, a large-scale image retrieval system for the
WWW. It handles over 3 million images to date. The system
retrieves images based on visual features and collateral
text. We show that a search process which consists of an
initial query-by-keyword or query-by-image and followed by
relevance feedback on the visual appearance of the results
is possible for large-scale data sets. We also show that it is
superior to the pure text retrieval commonly used in largescale
systems. Semantic relationships in the data are explored
and exploited by data mining, and multiple feature
spaces are included in the search process.
Download in pdf format
@InProceedings{eth_biwi_00522,
author = {T. Quack and U. M\"onich and L. Thiele and B.S. Manjunath},
title = {Cortina: A System for Large-scale, Content-based Web Image Retrieval},
booktitle = {ACM Multimedia 2004, New York, NY, USA, Oct. 2004},
year = {2004},
keywords = {}
}