prikaz prve stranice dokumenta Procjena poze sportaša temeljeno na dubokom učenju
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master's thesis
Procjena poze sportaša temeljeno na dubokom učenju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:091818
Hadžimuratagić, Anel
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Hadžimuratagić, A. (2021). Procjena poze sportaša temeljeno na dubokom učenju (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:091818

Hadžimuratagić, Anel. "Procjena poze sportaša temeljeno na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:091818

Hadžimuratagić, Anel. "Procjena poze sportaša temeljeno na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:091818

Hadžimuratagić, A. (2021). 'Procjena poze sportaša temeljeno na dubokom učenju', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 23 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:091818

Hadžimuratagić A. Procjena poze sportaša temeljeno na dubokom učenju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 July 23] Available at: https://urn.nsk.hr/urn:nbn:hr:168:091818

A. Hadžimuratagić, "Procjena poze sportaša temeljeno na dubokom učenju", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:091818

Metadata
TitleProcjena poze sportaša temeljeno na dubokom učenju
Title (english)Athletes Pose Estimation Based on Deep Learning
AuthorAnel Hadžimuratagić
MentorVladimir Čeperić (mentor)
Committee memberVladimir Čeperić (predsjednik povjerenstva)
Committee memberSiniša Šegvić (član povjerenstva)
Committee memberMirko Poljak (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Procjena poze je jedan od važnijih problema u području računalnog vida. U ovom radu upoznali smo se s najvažnijim primjenama procjene poze u sportu. Opisali smo što je duboko učenje te smo se upoznali s njegovim ključnim dijelovima. Prikazali smo glavne dijelove implementacije modela te predstavili dosadašnja istraživanja. Predstavili smo dva pristupa: odozgo prema dolje i odozdo prema gore koji smo koristili za implementaciju ovog problema. Detaljno smo opisali skup podataka Leeds Sport Pose te prikazali i opisali dobivene rezultate na tom skupu. Na kraju predložili moguća poboljšanja i nadogradnju modela.
Abstract (english)
Pose estimation is one of the biggest problems in computer vision area. In this paper you were introduced with the most important usage of pose estimation in sports. Deep learning was described along side its key features. Main parts of the model implementation were presented, as well as the previous researches. Two approaches were shown: top-up approach and bottom-up approach which we used for the implementation. In addition, we have explained in detail the Leeds Sport Pose dataset and presented the results of the work. In the end, we suggested possible improvements and upgrades of our problem.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:091818
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-13 12:23:49