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master's thesis
Sustav za praćenje pogleda zasnovan na strojnom učenju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:976975
Assouline, Nicolas
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Assouline, N. (2022). Sustav za praćenje pogleda zasnovan na strojnom učenju (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:976975

Assouline, Nicolas. "Sustav za praćenje pogleda zasnovan na strojnom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:976975

Assouline, Nicolas. "Sustav za praćenje pogleda zasnovan na strojnom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:976975

Assouline, N. (2022). 'Sustav za praćenje pogleda zasnovan na strojnom učenju', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 02 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:976975

Assouline N. Sustav za praćenje pogleda zasnovan na strojnom učenju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 July 02] Available at: https://urn.nsk.hr/urn:nbn:hr:168:976975

N. Assouline, "Sustav za praćenje pogleda zasnovan na strojnom učenju", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:976975

Metadata
TitleSustav za praćenje pogleda zasnovan na strojnom učenju
Title (english)Gaze Tracking System Based on Machine Learning
AuthorNicolas Assouline
MentorMarin Šilić (mentor)
Committee memberMarin Šilić (predsjednik povjerenstva)
Committee memberSiniša Srbljić (član povjerenstva)
Committee memberGoran Delač (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-01, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Područje računalnog vida vrlo je široko. U ovom radu predstavljene su moderne metode prepoznavanja i procjene položaja lokacije pogleda na ekranu. Opisani su i implementirani pristupi problemu koji koriste hrbatnu regresiju i različite arhitekture konvolucijskih neuralnih mreža. Predstavljene su prednosti i mane svakog pristupa. Pomoću razvijene aplikacije moguće je u stvarnom vremenu pratiti korisnikov pogled po ekranu, čak i na slabijim računalima i računalima bez grafičkih kartica.
Abstract (english)
Computer vision is a very broad area. This thesis introduces approaches to machine learning-based gaze recognition and estimation using multiple techniques, including ridge regression and convolutional neural networks. It discusses the pros and cons of each approach. As part of this thesis, a desktop application capable of real-time gaze estimation has been developed. The app performs well, even on low-spec computers and computers without discrete GPUs.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:976975
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 on2023-01-13 14:23:50