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master's thesis
Metode za procjenu ljudske poze
2023. urn:nbn:hr:168:602105
Popović, Danijel
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Popović, D. (2023). Metode za procjenu ljudske poze (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:602105

Popović, Danijel. "Metode za procjenu ljudske poze." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:602105

Popović, Danijel. "Metode za procjenu ljudske poze." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:602105

Popović, D. (2023). 'Metode za procjenu ljudske poze', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 09 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:602105

Popović D. Metode za procjenu ljudske poze [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 May 09] Available at: https://urn.nsk.hr/urn:nbn:hr:168:602105

D. Popović, "Metode za procjenu ljudske poze", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:602105

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Metadata
TitleMetode za procjenu ljudske poze
Title (english)Methods for Human Pose Estimation
AuthorDanijel Popović
MentorTomislav Pribanić (mentor)
Committee memberTomislav Pribanić (predsjednik povjerenstva)
Committee memberMarko Subašić (član povjerenstva)
Committee memberDarko Vasić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-02-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Svakodnevni susret sa sustavima koji koriste metode računalnog vida je neizbježan. Zahvaljujući dubokom učenju problemi računalnog vida ponovno postaju jako popularni. Među jednim od najzanimljivijih jest procjena ljudske poze u 2D/3D. U ovom radu istražene su te potom opisane metode standardnog (klasičnog) pristupa te pristupa koji koriste duboko učenje. Unutar te podjele naglašene su razlike njihovih pristupa i detaljno opisani postupci njihovih najboljih metoda. Implementirane su dvije metode za procjenu poze te je napravljena evaluacije provedenih eksperimenata i službenih rješenja.
Abstract (english)
Everyday encounter with systems that use computer vision methods is inevitable. Thanks to deep learning, computer vision problems are becoming very popular again. Among one of the most interesting is the estimation of human pose in 2D/3D. In this paper, the methods of the standard (classical) approach and approaches that use deep learning were investigated and then described. Within that division, the differences in their approaches are emphasized and the procedures of their best methods are described in detail. Two methods for pose estimation were implemented and an evaluation of the conducted experiments and official solutions was made.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:602105
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
Access conditionsClosed access
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Created on2023-07-13 10:29:15