Visual saliency detection via hypergraph based re-ranking using background priors
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Kyung wook | - |
dc.contributor.author | Lee, Dong ho | - |
dc.date.accessioned | 2021-06-22T21:42:32Z | - |
dc.date.available | 2021-06-22T21:42:32Z | - |
dc.date.created | 2021-01-22 | - |
dc.date.issued | 2015-01 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/20581 | - |
dc.description.abstract | Salient object detection is a powerful tool to be applied to many computer vision tasks such as object recognition, image segmentation and scene understanding. We formulate salient object detection as a hypergraph based ranking problem which ranks the similarity of the image elements with foreground or background cues. In addition, we introduce an adaptive background prior to prevent suppression of salient objects touching image boundary. We can improve the results of saliency detection by using the adaptive background priors. Experimental results on three public image dataset demonstrate that our method performs better than the state-of-the-art saliency detection methods. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Association for Computing Machinery, Inc | - |
dc.title | Visual saliency detection via hypergraph based re-ranking using background priors | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Dong ho | - |
dc.identifier.doi | 10.1145/2701126.2701134 | - |
dc.identifier.scopusid | 2-s2.0-84926200379 | - |
dc.identifier.wosid | 000380586500061 | - |
dc.identifier.bibliographicCitation | ACM IMCOM 2015 - Proceedings | - |
dc.relation.isPartOf | ACM IMCOM 2015 - Proceedings | - |
dc.citation.title | ACM IMCOM 2015 - Proceedings | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.subject.keywordPlus | Computer vision | - |
dc.subject.keywordPlus | Image segmentation | - |
dc.subject.keywordPlus | Information management | - |
dc.subject.keywordPlus | Object recognition | - |
dc.subject.keywordPlus | Adaptive backgrounds | - |
dc.subject.keywordPlus | Hypergraph | - |
dc.subject.keywordPlus | Image boundaries | - |
dc.subject.keywordPlus | Saliency detection | - |
dc.subject.keywordPlus | Salient object detection | - |
dc.subject.keywordPlus | Scene understanding | - |
dc.subject.keywordPlus | State of the art | - |
dc.subject.keywordPlus | Visual saliency detections | - |
dc.subject.keywordPlus | Object detection | - |
dc.subject.keywordAuthor | Adaptive background prior | - |
dc.subject.keywordAuthor | Hypergraph based ranking | - |
dc.subject.keywordAuthor | Salient object detection | - |
dc.identifier.url | https://dl.acm.org/doi/10.1145/2701126.2701134 | - |
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