Title :
An Unified Framework Based on p-Norm for Feature Aggregation in Content-Based Image Retrieval
Author :
Zhang, Jun ; Ye, Lei
Author_Institution :
Univ. of Wollongong, Wollongong
Abstract :
Feature aggregation is a critical technique in content- based image retrieval systems that employ multiple visual features to characterize image content. In this paper, the p-norm is introduced to feature aggregation that provides a framework to unify various previous feature aggregation schemes such as linear combination, Euclidean distance, Boolean logic and decision fusion schemes in which previous schemes are instances. Some insights of the mechanism of how various aggregation schemes work are discussed through the effects of model parameters in the unified framework. Experiments show that performances vary over feature aggregation schemes that necessitates an unified framework in order to optimize the retrieval performance according to individual queries and user query concept. Revealing experimental results conducted with IAPR TC-12 ImageCLEF2006 benchmark collection that contains over 20,000 photographic images are presented and discussed.
Keywords :
content-based retrieval; image retrieval; Boolean logic; Euclidean distance; content-based image retrieval; decision fusion schemes; feature aggregation; image content; linear combination; p-norm; retrieval performance; Boolean functions; Computer science; Content based retrieval; Euclidean distance; Fuzzy logic; Image retrieval; Information retrieval; Multimedia systems; Software engineering; Vectors;
Conference_Titel :
Multimedia, 2007. ISM 2007. Ninth IEEE International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-0-7695-3058-1
DOI :
10.1109/ISM.2007.4412374