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master's thesis
Raspoznavanje gesti ruku konvolucijskim modelima
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:490254
Bronić, Filip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bronić, F. (2020). Raspoznavanje gesti ruku konvolucijskim modelima (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:490254

Bronić, Filip. "Raspoznavanje gesti ruku konvolucijskim modelima." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:490254

Bronić, Filip. "Raspoznavanje gesti ruku konvolucijskim modelima." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:490254

Bronić, F. (2020). 'Raspoznavanje gesti ruku konvolucijskim modelima', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 August 2024, https://urn.nsk.hr/urn:nbn:hr:168:490254

Bronić F. Raspoznavanje gesti ruku konvolucijskim modelima [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 August 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:490254

F. Bronić, "Raspoznavanje gesti ruku konvolucijskim modelima", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:490254

Metadata
TitleRaspoznavanje gesti ruku konvolucijskim modelima
Title (english)Recognition of hand gestures with convolutional models
AuthorFilip Bronić
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberZoran Kalafatić (član povjerenstva)
Committee memberVladimir Čeperić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-09-24, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Raspoznavanje gesti ruku je neriješen problem računalnog vida s mnogim zanimljivim primjenama. U posljednje vrijeme, najbolji rezultati u tom području postižu se dubokim konvolucijskim modelima. U ovom radu se za raspoznavanje gesti ruku iz RGB videosnimki koriste 3D konvolucijske neuronske mreže koje su se pokazale uspješnima u tom području: arhitekture SlowFast i MobileNetV2. Koristeći navedene modele implementiran je sustav za dinamičko prepoznavanje gesti u stvarnom vremenu. Modeli su trenirani i evaluirani na podskupu Jester skupa podataka. Prezentirani su rezultati modela i predloženi pravci za daljnji rad.
Abstract (english)
Hand gesture recognition is a challenging computer vision problem with many practical uses. Recently, best results have been achieved by deep convolutional models. In this work, for hand gesture recognition in RGB videos 3D convolutional neural networks are used that have achieved great results in the field, architectures SlowFast and MobileNetV2. Using aforementioned architectures a real-time dynamic hand gesture recognition system is implemented. Models are trained and evaluated on a subset of the Jester dataset. Model results are presented and potential directions for future work are suggested.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:490254
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 11:54:14