Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/86424
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Folgado, Duarte | por |
dc.contributor.author | Barandas, Marília | por |
dc.contributor.author | Matias, Ricardo | por |
dc.contributor.author | Martins, Rodrigo | por |
dc.contributor.author | Carvalho, Miguel | por |
dc.contributor.author | Gamboa, Hugo | por |
dc.date.accessioned | 2023-09-18T12:37:05Z | - |
dc.date.available | 2023-09-18T12:37:05Z | - |
dc.date.issued | 2018 | - |
dc.identifier.issn | 0031-3203 | por |
dc.identifier.uri | https://hdl.handle.net/1822/86424 | - |
dc.description.abstract | When a comparison between time series is required, measurement functions provide meaningful scores to characterize similarity between sequences. Quite often, time series appear warped in time, i.e, although they may exhibit amplitude and shape similarity, they appear dephased in time. The most common al- gorithm to overcome this challenge is the Dynamic Time Warping, which aligns each sequence prior establishing distance measurements. However, Dynamic Time Warping takes only into account amplitude similarity. A distance which characterizes the degree of time warping between two sequences can deliver new insights for applications where the timing factor is essential, such well-defined movements during sports or rehabilitation exercises. We propose a novel measurement called Time Alignment Measurement, which delivers similarity information on the temporal domain. We demonstrate the potential of our ap- proach in measuring performance of time series alignment methodologies and in the characterization of synthetic and real time series data acquired during human movement. | por |
dc.description.sponsorship | This work was supported by North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM) [NORTE-01-0145-FEDER-000026]. | por |
dc.language.iso | eng | por |
dc.publisher | Elsevier 1 | por |
dc.relation | NORTE-01-0145-FEDER-000026 | por |
dc.rights | openAccess | por |
dc.subject | Time series | por |
dc.subject | Time warping | por |
dc.subject | Similarity | por |
dc.subject | Distance | por |
dc.subject | Signal alignment | por |
dc.title | Time alignment measurement for time series | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0031320318301286?via%3Dihub | por |
oaire.citationStartPage | 268 | por |
oaire.citationEndPage | 279 | por |
oaire.citationVolume | 81 | por |
dc.identifier.doi | 10.1016/j.patcog.2018.04.003 | por |
dc.subject.fos | Engenharia e Tecnologia::Outras Engenharias e Tecnologias | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Pattern Recognition | por |
oaire.version | VoR | por |
dc.subject.ods | Indústria, inovação e infraestruturas | por |
Aparece nas coleções: | DET/2C2T - Artigos em revistas internacionais com arbitragem científica |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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MAC-18-PR-1.pdf | 1,23 MB | Adobe PDF | Ver/Abrir |