Hybdrid Content Based Image Retrieval combining multi-objective interactive genetic algorithm and SVM
Inhaltsverzeichnis
Referenz
Romaric Pighetti; Denis Pallez; Frédéric Precioso: Hybdrid Content Based Image Retrieval combining multi-objective interactive genetic algorithm and SVM. Pattern Recognition (ICPR), 2012 21st International Conference on, 2849 - 2852.
DOI
Abstract
The amount of images contained in repositories or available on Internet has exploded over the last years. In order to retrieve efficiently one or several images in a database, the development of Content-Based Image Retrieval (CBIR) systems has become an intensively active research area. However, most proposed systems are keyword-based and few imply the end-user during the search (through relevance feedback). Visual low-level descriptors are then substituted to keywords but there is a gap between visual description and user expectations. We propose a new framework which combines a multi-objective interactive genetic algorithm, allowing a trade-off between image features and user evaluations, and a support vector machine to learn the user relevance feedback. We test our system on SIMPLIcity database, commonly used in the literature to evaluate CBIR systems using a genetic algorithm, and it outperforms the recent frameworks.
Extended Abstract
Bibtex
@INPROCEEDINGS{6460759,
author={R. Pighetti and D. Pallez and F. Precioso},
booktitle={Pattern Recognition (ICPR), 2012 21st International Conference on},
title={Hybdrid Content Based Image Retrieval combining multi-objective interactive genetic algorithm and SVM},
year={2012},
pages={2849-2852},
keywords={Internet;content-based retrieval;feature extraction;genetic algorithms;image retrieval;interactive systems;relevance feedback;support vector machines;visual databases;CBIR systems;Internet;SIMPLIcity database;SVM;hybrid content-based image retrieval;image database;image features;image repository;keyword-based system;multiobjective interactive genetic algorithm;support vector machine;user evaluation;user expectations;user relevance feedback;visual description;visual low-level descriptors;Genetic algorithms;Image retrieval;Sociology;Support vector machines;Training;Vectors},
ISSN={1051-4651},
month={Nov},
url={http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6460759 http://de.evo-art.org/index.php?title=Hybdrid_Content_Based_Image_Retrieval_combining_multi-objective_interactive_genetic_algorithm_and_SVM },
}
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