Praćenje smjera pogleda

Aleksa, Antun

prikaz prve stranice dokumenta Praćenje smjera pogleda

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master's thesis

Praćenje smjera pogleda

2017. urn:nbn:hr:168:694571

Aleksa, Antun

University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

APA 6th Edition

Aleksa, A. (2017). Praćenje smjera pogleda (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:694571

MLA 8th Edition

Aleksa, Antun. "Praćenje smjera pogleda." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:694571

Chicago 17th Edition

Aleksa, Antun. "Praćenje smjera pogleda." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:694571

Harvard

Aleksa, A. (2017). 'Praćenje smjera pogleda', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 February 2025, https://urn.nsk.hr/urn:nbn:hr:168:694571

Vancouver

Aleksa A. Praćenje smjera pogleda [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2017 [cited 2025 February 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:694571

IEEE

A. Aleksa, "Praćenje smjera pogleda", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:168:694571

Cite this item: https://urn.nsk.hr/urn:nbn:hr:168:694571

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Metadata

Title	Praćenje smjera pogleda
Title (english)	Gaze Tracking
Author	Antun Aleksa
Mentor	Igor Sunday Pandžić (mentor)
Committee member	Igor Sunday Pandžić (predsjednik povjerenstva)
Committee member	Željka Car (član povjerenstva)
Committee member	Marin Vuković (član povjerenstva)
Granter	University of Zagreb Faculty of Electrical Engineering and Computing Zagreb
Defense date and country	2017-07-06, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing
Abstract	Ovaj rad analizira moderne pristupe rješavanja problema praćenja pogleda i javno dostupnih baza podataka u svrhu testiranja metode koja je trenutno implementirana u sklopu razvojnog alata VisageSDK i stvaranja nove metode korištenjem pojačanih regresijskih stabala i linearne regresije temeljene na strojnom učenju. Rad opisuje proceduru skupljanja vlastite baze podataka sastavljene od 126 subjekata različite dobi i spola. Uz pomoć tog skupa podataka bilo je moguće testirati i usporediti rezultate dvije navedene metode.
Abstract (english)	This thesis analyses state-of-the-art gaze estimation methods and publicly free datasets in the purpose of testing a method currently implemented in VisageSDK and creating a new appearance-based method based on boosted regression trees and linear regression. It covers the procedure of collecting a completely new dataset consisted of 126 subjects of different gender and age. By using this dataset it was possible to test and compare the results of the two methods.
Keywords
Keywords (english)
Language	english
URN:NBN	urn:nbn:hr:168:694571
Study programme	Title: Computing Study programme type: university Study level: graduate Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resource	Text
File origin	Born digital
Access conditions	Closed access
Terms of use
Public note
Created on	2019-03-13 18:35:24