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master's thesis
Object tracking algorithms
Zagreb: University of Zagreb, Faculty of Science, 2021. urn:nbn:hr:217:699699
Pavlinić, Nikola
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Pavlinić, N. (2021). Object tracking algorithms (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:699699

Pavlinić, Nikola. "Object tracking algorithms." Master's thesis, University of Zagreb, Faculty of Science, 2021. https://urn.nsk.hr/urn:nbn:hr:217:699699

Pavlinić, Nikola. "Object tracking algorithms." Master's thesis, University of Zagreb, Faculty of Science, 2021. https://urn.nsk.hr/urn:nbn:hr:217:699699

Pavlinić, N. (2021). 'Object tracking algorithms', Master's thesis, University of Zagreb, Faculty of Science, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:217:699699

Pavlinić N. Object tracking algorithms [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2021 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:217:699699

N. Pavlinić, "Object tracking algorithms", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:217:699699

Metadata
TitleObject tracking algorithms
Title (croatian)Algoritmi za praćenje objekata
AuthorNikola Pavlinić
MentorBojan Basrak (mentor)
Committee memberBojan Basrak (predsjednik povjerenstva)
Committee memberDrago Špoljarić (član povjerenstva)
Committee memberMatej Mihelčić (član povjerenstva)
Committee memberJosip Tambača (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2021-07-21, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
U ovom diplomskom radu predstavljene su tri poznate metode za praćenje objekata, Kalmanov filter, point mass filter te filter čestica (particle filter). Kako su sva tri filtera zasnovana na Bayesovoj logici na početku se gradila teorija koja je potom primjenjena na sva tri filtera. Naposljetku smo naveli primjenu Kalmanovog filtera na simuliranim podacima.
Abstract (english)
This master thesis is presenting three well-known methods for monitoring objects, Kalman filter, point mass filter and particle filter. The theory was initially built through recursive Bayesian solution because all three methods are based on Bayesian Logic. Finally, we present an application of Kalman filter on a simulated data set under several different scenarios.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:699699
Study programmeTitle: Finance and Business Mathematics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-09-16 11:33:27