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An unified framework based on p-norm for feature aggregation in content-based image retrieval

conference contribution
posted on 2023-02-06, 03:42 authored by Jun Zhang, L Ye
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. © 2007 IEEE.

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Pagination

195 - 201

ISBN-13

9780769530581

ISBN-10

0769530583

Title of proceedings

Proceedings - 9th IEEE International Symposium on Multimedia, ISM 2007

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