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master's thesis
Raspoznavanje izraza lica temeljeno na dubokom učenju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:228203
Šesto, Franko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Šesto, F. (2019). Raspoznavanje izraza lica 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:168:228203

Šesto, Franko. "Raspoznavanje izraza lica temeljeno na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:228203

Šesto, Franko. "Raspoznavanje izraza lica temeljeno na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:228203

Šesto, F. (2019). 'Raspoznavanje izraza lica temeljeno na dubokom učenju', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 August 2024, https://urn.nsk.hr/urn:nbn:hr:168:228203

Šesto F. Raspoznavanje izraza lica temeljeno na dubokom učenju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 August 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:228203

F. Šesto, "Raspoznavanje izraza lica temeljeno na dubokom učenju", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:228203

Metadata
TitleRaspoznavanje izraza lica temeljeno na dubokom učenju
Title (english)Facial Expression Recognition Based on Deep Learning
AuthorFranko Šesto
MentorZoran Kalafatić (mentor)
Committee memberZoran Kalafatić (predsjednik povjerenstva)
Committee memberSiniša Šegvić (član povjerenstva)
Committee memberTomislav Hrkać (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-11, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Analiza i raspoznavanje izraza lica je jedno od trenutno popularnih područja koje ima zanimljive primjene u sustavima za interakciju čovjeka i računala. U ovom radu fokus je na dva bitna dijela koji određuju kvalitetu sustava: praćenju lica te klasifikaciji emocija izraženih ekspresijama lica. Praćenje lica je izazovan problem zbog velike različitosti lica i ekspresija lica te različitosti okolina u kojima se ona nalaze. Rješenje je teško dobiti zbog varijacija u osvijetljenosti, perspektivi lica te ekspresiji lica u različitim okolinama. Opisani su raznovrsni algoritmi u tom području te su iskorišteni za dobivanje dobrog praćenja kao potrebnog dijela sustava. S druge strane, za raspoznavanje emocija se koriste konvolucijske neuronske mreže. Opisano je kako funkcioniraju i koja su njihova dobra svojstva kao i dobri obrasci za dizajn arhitektura i treniranje mreža. Razmotrene su korištene arhitekture kao i dobivene točnosti na korištenom skupu slika. Na kraju su oba dijela ukomponirana u sustav koji raspoznaje emocije čovjeka u stvarnom vremenu.
Abstract (english)
Facial expression recognition and analysis is one of the currently popular areas that has interesting applications in human-computer interaction. This thesis is focused on two essential parts which decide system quality: face tracking and emotion classification based on facial expressions. Face tracking is a challenging problem, due to the large variability of faces and facial expressions, and context where they can be found. It is very difficult to come up with good solution due to the light variations, pose, different face expressions etc. Various algorithms are described from this area and they are used to get good tracking as necessary part of this system. On the other hand, convolutional neural networks are used for emotion recognition. It is described how they function and what are their good properties and good patterns for architecture design and network training. Various network architectures are trained on a large dataset and accuracies for those architectures are obtained. Both parts are combined into system able to recognize human emotions in real time.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:228203
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
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Created on2020-01-07 22:20:01