Movement in video classification using structured data : Workout videos application

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dc.contributor.advisorTabares Betancur, Marta Silviaspa
dc.contributor.authorMúnera Muñoz, Jonathan Damián
dc.coverage.spatialMedellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degreeseng
dc.creator.degreeMagíster en Ingenieríaspa
dc.creator.emailjdmuneram@eafit.edu.cospa
dc.date.accessioned2023-08-22T19:56:38Z
dc.date.available2023-08-22T19:56:38Z
dc.date.issued2023
dc.description.abstractNowadays, several video movement classification methodologies are based on reading and processing each frame using image classification algorithms. However, it is rare to find approaches using angle distribution over time. This paper proposes video movement classification based on the exercise states calculated from each frame's angles. Different video classification approaches and their respective variables and models were analyzed to achieve this, using unstructured data: images. Besides, structure data as angles from critical joints Armpits, legs, elbows, hips, and torso inclination were calculated directly from workout videos, allowing the implementation of classification models such as the KNN and Decision Trees. The result shows these techniques can achieve similar accuracy, close to 95\%, concerning Neural Networks algorithms, the primary model used in the previously mentioned approaches. Finally, it was possible to conclude that using structured data for movement classification models allows for lower performance costs and computing resources than using unstructured data without compromising the quality of the model.spa
dc.formatapplication/pdfeng
dc.identifier.ddc006.696 M965
dc.identifier.urihttp://hdl.handle.net/10784/32815
dc.language.isospaspa
dc.publisherUniversidad EAFITspa
dc.publisher.departmentEscuela de Ciencias Aplicadas e Ingenieríaspa
dc.publisher.placeMedellínspa
dc.publisher.programMaestría en Ingenieríaspa
dc.rightsTodos los derechos reservadosspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.localAcceso abiertospa
dc.subjectVisión computacionalspa
dc.subjectRedes neuronalesspa
dc.subjectProcesamiento de imagenspa
dc.subject.keywordMachine learningspa
dc.subject.keywordDeep learningspa
dc.subject.lembAPRENDIZAJE AUTOMÁTICO (INTELIGENCIA ARTIFICIAL)spa
dc.subject.lembALGORITMOS (COMPUTADORES)spa
dc.subject.lembPROCESAMIENTO DE IMÁGENESspa
dc.titleMovement in video classification using structured data : Workout videos applicationspa
dc.typemasterThesiseng
dc.typeinfo:eu-repo/semantics/masterThesiseng
dc.type.hasVersionacceptedVersioneng
dc.type.localTesis de Maestríaspa
dc.type.spaArtículospa

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