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dc.contributor.authorThambawita, Vajira
dc.contributor.authorHicks, Steven
dc.contributor.authorBorgli, Hanna
dc.contributor.authorStensland, Håkon Kvale
dc.contributor.authorJha, Debesh
dc.contributor.authorSvensen, Martin Kristoffer
dc.contributor.authorPettersen, Svein Arne
dc.contributor.authorJohansen, Dag
dc.contributor.authorJohansen, Håvard D.
dc.contributor.authorPettersen, Susann Dahl
dc.contributor.authorNordvang, Simon
dc.contributor.authorPedersen, Sigurd
dc.contributor.authorGjerdrum, Anders Tungeland
dc.contributor.authorGrønli, Tor-Morten
dc.contributor.authorFredriksen, Per Morten
dc.contributor.authorEg, Ragnhild
dc.contributor.authorHansen, Kjeld S.
dc.contributor.authorFagernes, Siri
dc.contributor.authorClaudi, Christine
dc.contributor.authorBiørn-Hansen, Andreas
dc.contributor.authorDang Nguyen, Duc Tien
dc.contributor.authorKupka, Tomas
dc.contributor.authorHammer, Hugo Lewi
dc.contributor.authorJain, Ramesh
dc.contributor.authorRiegler, Michael
dc.contributor.authorHalvorsen, Pål
dc.date.accessioned2020-12-28T08:50:51Z
dc.date.accessioned2021-02-19T12:50:04Z
dc.date.available2020-12-28T08:50:51Z
dc.date.available2021-02-19T12:50:04Z
dc.date.issued2020-05-27
dc.identifier.citationThambawita V, Hicks S, Borgli H, Stensland H, Jha D, Svensen MK, Pettersen SA, Johansen D, Johansen HJ, Pettersen SD, Nordvang S, Pedersen S, Gjerdrum AT, Grønli TMG, Fredriksen PM, Eg R, Hansen KSH, Fagernes S, Claudi C, Biørn-Hansen A, Dang Nguyen DT, Kupka T, Hammer HL, Jain R, Riegler M, Halvorsen P: PMData: a sports logging dataset. In: Alay OA, Toni L. MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference, 2020. Association for Computing Machinery (ACM) p. 231-236en
dc.identifier.isbn978-1-4503-6845-2
dc.identifier.urihttps://hdl.handle.net/10642/9636
dc.description.abstractIn this paper, we present PMData: a dataset that combines traditional lifelogging data with sports-activity data. Our dataset enables the development of novel data analysis and machine-learning applications where, for instance, additional sports data is used to predict and analyze everyday developments, like a person's weight and sleep patterns; and applications where traditional lifelog data is used in a sports context to predict athletes' performance. PMData combines input from Fitbit Versa 2 smartwatch wristbands, the PMSys sports logging smartphone application, and Google forms. Logging data has been collected from 16 persons for five months. Our initial experiments show that novel analyses are possible, but there is still room for improvement.en
dc.language.isoenen
dc.publisherAssociation for Computing Machinery (ACM)en
dc.relation.ispartofMMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference
dc.relation.ispartofseriesMM: International Multimedia Conference;MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference
dc.subjectMultimedia datasetsen
dc.subjectNeural networksen
dc.subjectMachine learningen
dc.subjectSports loggingen
dc.subjectSensor dataen
dc.subjectFood picturesen
dc.titlePMData: a sports logging dataseten
dc.typeConference objecten
dc.date.updated2020-12-28T08:50:51Z
dc.description.versionpublishedVersionen
dc.identifier.doihttps://doi.org/10.1145/3339825.3394926
dc.identifier.cristin1819192
dc.relation.projectIDNorges forskningsråd: 263248
dc.source.isbn978-1-4503-6845-2


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