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master's thesis
Sustav za raspoznavanje gesta hrvatskoga znakovnog jezika
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:570125
Tomažin, Nikola
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Tomažin, N. (2022). Sustav za raspoznavanje gesta hrvatskoga znakovnog jezika (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:570125

Tomažin, Nikola. "Sustav za raspoznavanje gesta hrvatskoga znakovnog jezika." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:570125

Tomažin, Nikola. "Sustav za raspoznavanje gesta hrvatskoga znakovnog jezika." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:570125

Tomažin, N. (2022). 'Sustav za raspoznavanje gesta hrvatskoga znakovnog jezika', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 28 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:570125

Tomažin N. Sustav za raspoznavanje gesta hrvatskoga znakovnog jezika [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 28] Available at: https://urn.nsk.hr/urn:nbn:hr:168:570125

N. Tomažin, "Sustav za raspoznavanje gesta hrvatskoga znakovnog jezika", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:570125

Metadata
TitleSustav za raspoznavanje gesta hrvatskoga znakovnog jezika
Title (english)System for Recognition of Croatian Sign Language Gestures
AuthorNikola Tomažin
MentorTomislav Hrkać (mentor)
Committee memberTomislav Hrkać (predsjednik povjerenstva)
Committee memberVladimir Čeperić (član povjerenstva)
Committee memberZoran Kalafatić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-11, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Raspoznavanje gesta znakovnoga jezika veoma je kompleksan problem koji se prvotno temelji na kvalitetnoj procjeni poze. U ovom su radu dane teorijske osnove znakovnoga jezika (u čemu su puno pomogli članovi Hrvatskog saveza gluhih i nagluhih) te strojnog i dubokog učenja te je napravljena usporedba raznih alata procjene poze, od kojih se MediaPipe biblioteka najviše istaknula svojom robusnošcu i radom u stvarnom vremenu. Razvijen je sustav za izgradnju podatkovnoga skupa, treniranje sustava te testiranje preko racunalnoga programa i preko web sučelja.
Abstract (english)
Recognizing sign language gestures is a very complex problem, which is initially based on a quality pose estimation. This thesis presents the theoretical foundations of sign language (where members of the Croatian Association of the Deaf and Hard of Hearing helped a lot), machine and deep learning, and a comparison of various pose estimation tools, of which MediaPipe stood out for its robustness and real-time work. A system for building a dataset, system training and testing via a computer program and via a web interface has been developed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:570125
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 14:01:57