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dc.contributor.advisorPettersen, Robert
dc.contributor.advisorJohansen, Dag
dc.contributor.authorNordmo, Tor-Arne Schmidt
dc.date.accessioned2018-07-04T08:03:17Z
dc.date.available2018-07-04T08:03:17Z
dc.date.issued2018-06-01
dc.description.abstractThe advances in sensor technology and big-data processing enable performance analysis of sport athletes. With the increase in data, both from on-body sensors and cameras, it is possible to quantify what makes a good athlete. However, typical approaches in sports performance analysis are not adequately equipped for automatically handling big data. This thesis presents Arctic Human Activity Recognition on the Edge, a machine-learning based system that aims to provide live performance analysis of cross-country skiers. Arctic HARE uses on-body sensors and cameras to capture movement of the skier, and provides classification of the perceived technique. We explore and compare two approaches to classifying data, in order to determine optimal representations that embody the movement of the skier. The viability of Arctic HARE is substantiated through a working prototype. We ascertain how to optimally capture the movement of the skier and we qualitatively compare the two approaches through experimental evaluation. Our results reveal we can achieve as high as 97% accuracy for real-time classification of cross-country techniques.en_US
dc.identifier.urihttps://hdl.handle.net/10037/13142
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2018 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)en_US
dc.subject.courseIDINF-3981
dc.subjectVDP::Technology: 500::Information and communication technology: 550::Computer technology: 551en_US
dc.subjectVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Datateknologi: 551en_US
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420::System development and system design: 426en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Systemutvikling og – arbeid: 426en_US
dc.titleArctic HARE. A Machine Learning-based System for Performance Analysis of Cross-country Skiersen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


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Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)