Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/23230
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Jardim, D. | - |
dc.contributor.author | Nunes, L. | - |
dc.contributor.author | Dias, M. | - |
dc.contributor.editor | Van Harmelen, F., Dignum, V., Dignum, F., Bouquet, P., Fox, M., Kaminka, G. A., and Hüllermeier, E. | - |
dc.date.accessioned | 2021-09-27T14:51:41Z | - |
dc.date.available | 2021-09-27T14:51:41Z | - |
dc.date.issued | 2016 | - |
dc.identifier.isbn | 978-1-61499-672-9 | - |
dc.identifier.uri | http://hdl.handle.net/10071/23230 | - |
dc.description.abstract | For many applications it is important to be able to detect what a human is currently doing. This ability is useful for applications such as surveillance, human computer interfaces, games and healthcare. In order to recognize a human action, the typical approach is to use manually labeled data to perform supervised training. This paper aims to compare the performance of several supervised classifiers trained with manually labeled data versus the same classifiers trained with data automatically labeled. In this paper we propose a framework capable of recognizing human actions using supervised classifiers trained with automatically labeled data in RGB-D videos. | eng |
dc.language.iso | eng | - |
dc.publisher | IOS Press | - |
dc.relation | info:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBDE%2F52125%2F2013/PT | - |
dc.rights | openAccess | - |
dc.title | Impact of automated action labeling in classification of human actions in RGB-D videos | eng |
dc.type | conferenceObject | - |
dc.event.title | 22nd European Conference on Artificial Intelligence, ECAI 2016 | - |
dc.event.type | Conferência | pt |
dc.event.location | The Hage | eng |
dc.event.date | 2016 | - |
dc.pagination | 1632 - 1633 | - |
dc.peerreviewed | no | - |
dc.journal | ECAI 2016: 22nd European Conference on Artificial Intelligence | - |
dc.volume | 285 | - |
degois.publication.firstPage | 1632 | - |
degois.publication.lastPage | 1633 | - |
degois.publication.location | The Hage | eng |
degois.publication.title | Impact of automated action labeling in classification of human actions in RGB-D videos | eng |
dc.date.updated | 2021-09-27T15:43:52Z | - |
dc.description.version | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.doi | 10.3233/978-1-61499-672-9-1632 | - |
dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação | por |
iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-42665 | - |
iscte.alternateIdentifiers.wos | WOS:000385793700220 | - |
iscte.alternateIdentifiers.scopus | 2-s2.0-85013073342 | - |
Aparece nas coleções: | ISTAR-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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conferenceobject_42665.pdf | Versão Editora | 131,13 kB | Adobe PDF | Ver/Abrir |
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