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master's thesis
Detekcija i praćenje igrača u sportskom videu
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:313575
Vitlov, Mihael
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Vitlov, M. (2023). Detekcija i praćenje igrača u sportskom videu (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:313575

Vitlov, Mihael. "Detekcija i praćenje igrača u sportskom videu." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:313575

Vitlov, Mihael. "Detekcija i praćenje igrača u sportskom videu." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:313575

Vitlov, M. (2023). 'Detekcija i praćenje igrača u sportskom videu', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:313575

Vitlov M. Detekcija i praćenje igrača u sportskom videu [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 May 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:313575

M. Vitlov, "Detekcija i praćenje igrača u sportskom videu", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:313575

Metadata
TitleDetekcija i praćenje igrača u sportskom videu
Title (english)Detection and tracking of players in sport video
AuthorMihael Vitlov
MentorZoran Kalafatić (mentor)
Committee memberZoran Kalafatić (predsjednik povjerenstva)
Committee memberTomislav Hrkać (član povjerenstva)
Committee memberSiniša Šegvić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-10, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu razmatramo problem detekcije i praćenja nogometaša u video snimkama. Ovaj problem sadržava male objekte koji se brzo kreću, međusobno preklapaju i variraju u veličini. U radu su objašnjene konvolucijske neuronske mreže, algoritmi detekcije i algoritmi praćenja. Implementiran je sustav za detekciju igrača temeljen na algoritmima dubokog učenja YOLOv5 i YOLOv8, a praćenje je ostvareno SORT i deepSORT algoritmima. Rezultati sustava se vizualiziraju i vrednuju računanjem kvantitativnih MOT16 metrika. U radu su na petominutnom videu ostvareni zadovoljavajući rezultati MOTA mjere od 65%.
Abstract (english)
In this paper, we consider the problem of detecting and tracking football players in sports video. This problem involves small objects that move quickly, overlap each other, and vary in size. Convolutional neural networks, detection algorithms and tracking algorithms are explained in the paper. A player detection system based on the YOLOv5 and YOLOv8 deep learning algorithms was implemented, and tracking was achieved using SORT and deepSORT algorithms. The results of the system are visualized and evaluated by calculating quantitative MOT16 metrics. The results of the MOTA metric of 65% were achieved on a five-minute video.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:313575
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 on2023-10-11 10:54:45