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master's thesis
Određivanje poze osoba temeljeno na dubokom učenju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:242552
Ilić, Petra
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Ilić, P. (2023). Određivanje poze osoba temeljeno na dubokom učenju (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:242552

Ilić, Petra. "Određivanje poze osoba temeljeno na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:242552

Ilić, Petra. "Određivanje poze osoba temeljeno na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:242552

Ilić, P. (2023). 'Određivanje poze osoba temeljeno na dubokom učenju', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:242552

Ilić P. Određivanje poze osoba temeljeno na dubokom učenju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 May 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:242552

P. Ilić, "Određivanje poze osoba temeljeno na dubokom učenju", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:242552

Metadata
TitleOdređivanje poze osoba temeljeno na dubokom učenju
Title (english)Human pose estimation based on deep learning
AuthorPetra Ilić
MentorZoran Kalafatić (mentor)
Committee memberZoran Kalafatić (predsjednik povjerenstva)
Committee memberTomislav Hrkać (član povjerenstva)
Committee memberDomagoj Jakobović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-03, Croatia
Abstract
Određivanje poze osoba je popularan problem u području računalnog vida koji obuhvaća detekciju, povezivanje i praćenje ključnih točaka tijela poput zglobova ruku i nogu, torza i glave. Ovaj rad istražuje primjenu određivanja poze ruku u svrhu automatskog prepoznavanja znakovnog jezika, s fokusom na olakšavanje komunikacije gluhonijemih osoba i poticanje prihvaćanja i razumijevanja znakovnog jezika u široj zajednici. U okviru rada razvijen je klasifikator za prepoznavanje znakova abecede američkog znakovnog jezika. Za ostvarivanje preciznog praćenja ključnih točaka ruke korištena je biblioteka MediaPipe Hands. Model za određivanje poze ruke generira ključne točke koje se potom koriste kao ulaz za klasifikator, koji prepoznaje specifične poze ruke povezane s određenim znakovima abecede znakovnog jezika. Razvijena je i jednostavna aplikacija koja pruža korisnicima interaktivno sučelje za učenje i vježbanje osnova znakovnog jezika.
Abstract (english)
Determining the pose of individuals is a popular problem in the field of computer vision, which involves the detection, association, and tracking of key body points such as joints of the arms and legs, the torso, and the head. This paper explores the application of hand pose estimation for automatic sign language recognition, with a focus on facilitating communication for deaf and mute individuals and promoting acceptance and understanding of sign language within the wider community. Within the scope of this study, a classifier for recognizing American Sign Language alphabet signs was developed. The MediaPipe Hands library was used to achieve accurate tracking of key hand points. The hand pose estimation model generates these points, which are then used as input for the classifier that recognizes specific hand poses associated with certain sign language alphabet characters. Additionally, a simple application was developed, providing users with an interactive interface for learning and practicing the fundamentals of sign language.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:242552
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
Terms of useLicence In copyright icon
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Created on2023-10-11 09:05:14