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undergraduate thesis
Prepoznavanje gesti na slikama
2020. urn:nbn:hr:168:935025
Popović, Danijel
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Popović, D. (2020). Prepoznavanje gesti na slikama (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:935025

Popović, Danijel. "Prepoznavanje gesti na slikama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:935025

Popović, Danijel. "Prepoznavanje gesti na slikama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:935025

Popović, D. (2020). 'Prepoznavanje gesti na slikama', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 11 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:935025

Popović D. Prepoznavanje gesti na slikama [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 November 11] Available at: https://urn.nsk.hr/urn:nbn:hr:168:935025

D. Popović, "Prepoznavanje gesti na slikama", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:935025

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Metadata
TitlePrepoznavanje gesti na slikama
Title (english)Gesture Recognition
AuthorDanijel Popović
MentorTomislav Pribanić (mentor)
Committee memberTomislav Pribanić (predsjednik povjerenstva)
Committee memberKristijan Bartol (član povjerenstva)
Committee memberDavid Bojanić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-09-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Rad opisuje uspješne i veoma popularne metode prepoznavanja gesti. Prepoznavanje se ostvaruje služeći se nekim oblikom umjetna inteligencije. Istražene su i razrađene metode obrade slika, računalnog vida te neuronskih mreža. Predstavljena je jednostavna implementacija metoda OpenCV biblioteke. Implementacija je rješavala problem prepoznavanja trenutnog broja podignutih prstiju snimljenih kamerom. Prikazani su rezultati implementacije te potom pristup je bio uspoređivan s kompleksnim metodama opisanih prethodno. Navode se i nedostatci implementacije i načini kako da se ona poboljša i unaprijedi.
Abstract (english)
This paper describes efficient and very popular methods for gesture recognition. Recognition si attained using some form of artificial intelligence. Image recognition, computer vision and neural network methods have been researched and explained. Simple solution using OpenCV libraries was demonstrated. The task it performed was recognition of the number of extended fingers on the screen. Results of the solution were shown and compared with the complex methods described earlier. Defects and improvements that can be made are also discussed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:935025
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-14 21:27:14