Automatic extraction of semantic relationships from images using ontologies and SVM classifiers
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jeong, Jin woo | - |
dc.contributor.author | Park, Kyung wook | - |
dc.contributor.author | Lee, Oukseh | - |
dc.contributor.author | Lee, Dong ho | - |
dc.date.accessioned | 2021-06-23T20:40:02Z | - |
dc.date.available | 2021-06-23T20:40:02Z | - |
dc.date.issued | 2007-07 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/44220 | - |
dc.description.abstract | Extracting high-level semantic concepts from low-level visual features of images is a very challenging research. Although traditional machine learning approaches just extract fragmentary information of images, their performance is still not satisfying. In this paper, we propose a novel system that automatically extracts high-level concepts such as spatial relationships or natural-enemy relationships from images using combination of ontologies and SVM classifiers. Our system consists of two phases. In the first phase, visual features are mapped to intermediate-level concepts (e.g, yellow, 45 angular stripes). And then, a set of these concepts are classified into relevant object concepts (e.g, tiger) by using SVM-classifiers. In this phase, revision module which improves the accuracy of classification is used. In the second phase, based on extracted visual information and domain ontology, we deduce semantic relationships such as spatial/natural-enemy relationships between multiple objects in an image. Finally, we evaluate the proposed system using color images including about 20 object concepts. © Springer-Verlag Berlin Heidelberg 2007. | - |
dc.format.extent | 11 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Springer Verlag | - |
dc.title | Automatic extraction of semantic relationships from images using ontologies and SVM classifiers | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1007/978-3-540-73417-8_25 | - |
dc.identifier.scopusid | 2-s2.0-37249082481 | - |
dc.identifier.wosid | 000247908900025 | - |
dc.identifier.bibliographicCitation | Multimedia Content Analysis and Mining International Workshop, MCAM 2007, Weihai, China, June 30-July 1, 2007, Proceedings, v.4577 LNCS, pp 184 - 194 | - |
dc.citation.title | Multimedia Content Analysis and Mining International Workshop, MCAM 2007, Weihai, China, June 30-July 1, 2007, Proceedings | - |
dc.citation.volume | 4577 LNCS | - |
dc.citation.startPage | 184 | - |
dc.citation.endPage | 194 | - |
dc.type.docType | Conference Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Imaging Science & Photographic Technology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Imaging Science & Photographic Technology | - |
dc.subject.keywordPlus | Image analysis | - |
dc.subject.keywordPlus | Learning systems | - |
dc.subject.keywordPlus | Ontology | - |
dc.subject.keywordPlus | Automatic image annotation | - |
dc.subject.keywordPlus | Semantic annotation | - |
dc.subject.keywordPlus | Content based retrieval | - |
dc.subject.keywordAuthor | Automatic image annotation | - |
dc.subject.keywordAuthor | Content-based image retrieval | - |
dc.subject.keywordAuthor | Machine learning | - |
dc.subject.keywordAuthor | Ontology | - |
dc.subject.keywordAuthor | Semantic annotation | - |
dc.subject.keywordAuthor | Support vector machine | - |
dc.identifier.url | https://link.springer.com/chapter/10.1007/978-3-540-73417-8_25 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.