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master's thesis
Detekcija i prepoznavanje lica koristeći Raspberry Pi računalo
2020. urn:nbn:hr:122:145017
Dubovečak, Mario
University North
University centre Varaždin
Department of Multimedia, Design and Application

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Dubovečak, M. (2020). Detekcija i prepoznavanje lica koristeći Raspberry Pi računalo (Master's thesis). Koprivnica: University North. Retrieved from https://urn.nsk.hr/urn:nbn:hr:122:145017

Dubovečak, Mario. "Detekcija i prepoznavanje lica koristeći Raspberry Pi računalo." Master's thesis, University North, 2020. https://urn.nsk.hr/urn:nbn:hr:122:145017

Dubovečak, Mario. "Detekcija i prepoznavanje lica koristeći Raspberry Pi računalo." Master's thesis, University North, 2020. https://urn.nsk.hr/urn:nbn:hr:122:145017

Dubovečak, M. (2020). 'Detekcija i prepoznavanje lica koristeći Raspberry Pi računalo', Master's thesis, University North, accessed 22 December 2024, https://urn.nsk.hr/urn:nbn:hr:122:145017

Dubovečak M. Detekcija i prepoznavanje lica koristeći Raspberry Pi računalo [Master's thesis]. Koprivnica: University North; 2020 [cited 2024 December 22] Available at: https://urn.nsk.hr/urn:nbn:hr:122:145017

M. Dubovečak, "Detekcija i prepoznavanje lica koristeći Raspberry Pi računalo", Master's thesis, University North, Koprivnica, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:122:145017

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Metadata
TitleDetekcija i prepoznavanje lica koristeći Raspberry Pi računalo
Title (english)Face detection and recognition using Raspberry Pi
AuthorMario Dubovečak
MentorEmil Dumić (mentor)
Committee memberMario Periša (predsjednik povjerenstva)
Committee memberRobert Geček (član povjerenstva)
Committee memberEmil Dumić (član povjerenstva)
GranterUniversity North
(University centre Varaždin)
(Department of Multimedia, Design and Application)
Koprivnica
Defense date and country2020-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Graphic Technology
Processes of Graphic Reproduction
Abstract
Ovim radom će se prikazati sustav za detekciju lica, te prepoznavanje lica iz unaprijed definirane baze koristeći Raspberry Pi računalo. Za detekciju lica mogu se koristiti različiti algoritmi poput Haarovih kaskada (Viola - Jones), histogrami orijentiranih gradijenata (HOG), metode potpornih vektora (SVM), te metode dubokog učenja koji će u teoretskom dijelu biti prikazani. Kao nastavak biti će prikazane neke postojeće metode koje se koriste za prepoznavanje lica poput Fisherfaces, Eigenfaces, histogrami lokalnih binarnih uzoraka, metode temeljene na SIFT i SURF deskriptorima i metode dubokog učenja zajedno sa primjerima koda u Python programskom jeziku. Kao završni dio ovog rada biti će prikazan praktični dio, odnosno uporaba Raspberry Pi računala sa pripadajućom opremom i programskom podrškom u svrhu detekcije i prepoznavanja lica uz pomoć unaprijed definirane baze.
Abstract (english)
This paper will show a face detection system, and face recognition from a predefined database using a Raspberry Pi computer. Different algorithms can be used for face detection, such as Haar cascades (Viola - Jones), oriented gradient histograms (HOG), support vector methods (SVM), and deep learning methods, which will be presented in the theoretical part. As a continuation, some existing methods used to recognize faces will be presented such as Fisherfaces, Eigenfaces, histograms of local binary patterns, methods based on SIFT and SURF descriptors and deep learning methods along with code examples in Python programming language. As the final part of this paper, the practical part will be presented, ie the use of Raspberry Pi computers with associated equipment and software for the purpose of face detection and recognition with the help of a predefined database.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:122:145017
Study programmeTitle: Multimedia Science
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka grafičke tehnologije (magistar/magistra inženjer/inženjerka grafičke tehnologije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-09-14 13:32:59