A relevance feedback approach for content based image retrieval using Gaussian mixture models
| dc.contributor.author | Marakakis, A. | en |
| dc.contributor.author | Galatsanos, N. | en |
| dc.contributor.author | Likas, A. | en |
| dc.contributor.author | Stafylopatis, A. | en |
| dc.date.accessioned | 2015-11-24T17:01:21Z | |
| dc.date.available | 2015-11-24T17:01:21Z | |
| dc.identifier.issn | 0302-9743 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/10910 | |
| dc.rights | Default Licence | - |
| dc.subject | bayesian framework | en |
| dc.subject | segmentation | en |
| dc.subject | system | en |
| dc.title | A relevance feedback approach for content based image retrieval using Gaussian mixture models | en |
| heal.abstract | In this paper a new relevance feedback (RF) methodology for content based image retrieval (CBIR) is presented. This methodology is based on Gaussian Mixture (GM) models for images. According to this methodology, the GM model of the query is updated in a probabilistic manner based on the GM models of the relevant images, whose relevance degree (positive or negative) is provided by the user. This methodology uses a recently proposed distance metric between probability density functions (pdfs) that can be computed in closed form for GM models. The proposed RF methodology takes advantage of the structure of this metric and proposes a method to update it very efficiently based on the GM models of the relevant and irrelevant images characterized by the user. We show with experiments the merits of the proposed methodology. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.journalName | Artificial Neural Networks - Icann 2006, Pt 2 | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2006 | - |
| heal.publisher | Springer | en |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικής | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
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