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master's thesis
Konvolucijski modeli za optički tok
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:956901
Anđelić, Antonio
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Anđelić, A. (2020). Konvolucijski modeli za optički tok (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:956901

Anđelić, Antonio. "Konvolucijski modeli za optički tok." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:956901

Anđelić, Antonio. "Konvolucijski modeli za optički tok." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:956901

Anđelić, A. (2020). 'Konvolucijski modeli za optički tok', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 04 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:956901

Anđelić A. Konvolucijski modeli za optički tok [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 November 04] Available at: https://urn.nsk.hr/urn:nbn:hr:168:956901

A. Anđelić, "Konvolucijski modeli za optički tok", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:956901

Metadata
TitleKonvolucijski modeli za optički tok
Title (english)Convolutional models for optical flow
AuthorAntonio Anđelić
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberSlobodan Ribarić (član povjerenstva)
Committee memberVlado Glavinić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Procjenjivanje optičkog toka neriješen je problem računalnog vida s mnogim zanimljivim primjenama. U posljednje vrijeme najbolja rješenja tog problema dobivaju se dubokim konvolucijskim modelima. Ovaj rad razmatra nadzirane pristupe kod kojih svaki par slika iz skupa za učenje mora biti označena gustim poljem točnog optičkog toka. U okviru rada, proučene su konvolucijske arhitekture za procjenu optičkog toka. Oblikovan je odgovarajući model i naučen na javno dostupnim skupovima. Mogućnost izvedbe na ugradbenom računalnom sustavu je procijenjena i opisana u sklopu rada. Hiperparametri su validirani, prikazani uz ostvarene rezultate koji su uspoređeni s rezultatima iz literature. Predložen je pravac budućeg razvoja. Uz rad je priložen izvorni kod razvijenih postupaka uz potrebna objašnjenja i dokumentaciju.
Abstract (english)
Optical flow estimation is an unsolved problem in computer vision with many interesting applications. Lately, the best results are achieved using deep convolutional models. This paper analyses approaches using supervised learning where each pair of images from training set has correctly annotated optical flow. In this paper, different convolutional models for optical flow estimation are described. One of those models was implemented and trained on publicly available datasets. Possibility of implementing that model on an embedded device was researched and described. Hyperparameters were validated and presented alongside the achieved results that were also compared to the results from the literature. Suggestion for future work is also described.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:956901
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 11:40:42