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scientific master's theses
Raspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2011. urn:nbn:hr:168:589348
Živić, Marijan
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Control and Computer Engineering

Institutional repository: FER Repository

Cite this document

Živić, M. (2011). Raspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi (Scientific master's theses). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:589348

Živić, Marijan. "Raspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2011. https://urn.nsk.hr/urn:nbn:hr:168:589348

Živić, Marijan. "Raspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2011. https://urn.nsk.hr/urn:nbn:hr:168:589348

Živić, M. (2011). 'Raspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 13 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:589348

Živić M. Raspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2011 [cited 2025 January 13] Available at: https://urn.nsk.hr/urn:nbn:hr:168:589348

M. Živić, "Raspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi", Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2011. Available at: https://urn.nsk.hr/urn:nbn:hr:168:589348

Metadata
TitleRaspoznavanje lica iz video zapisa na osnovu jednog uzorka za treniranje po osobi
AuthorMarijan Živić
MentorMario Kovač (mentor)
Committee memberMario Kovač (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Control and Computer Engineering)
Zagreb
Defense date and country2011, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Ovaj magistarski rad opisuje sustav za raspoznavanje lica iz video zapisa osobe. Osnovni uvjet sustava je korištenje jedne frontalne slike lica osobe u postupku treniranja. Frontalne slike lice su snimljene profesionalnim fotoaparatom i osvjetljenjem, slične su fotografijama koje se koriste za izradu identifikacijskih dokumenata. Sustav rješava problem poznat po nazivu „problem jednog uzorka za po osobi“. Predložen je novi sustav za rješavanje problema jednog uzorka po osobi. Sustav pronalazi preciznu lokaciju zjenica pomoću prstenastih Gaborovih filtera na osnovu koje se slike lica geometrijski normaliziraju. Na geometrijski normaliziranim slikama lica se izvodi normalizacija osvjetljenja. Prikazane su usporedbe metoda normalizacije osvjetljenja pomoću lokalnih binarnih uzoraka i gradijentnih lica. U provedenim eksperimentima je prikazana veća pogodnost metode gradijentnih lica. Također je pokazano kako sustavi raspoznavanja temeljeni na KPCA metodi daju značajno bolje rezultate na realnim video zapisima.
Abstract (english)
This master thesis represents face recognition system in video. The system is based on one image with frontal pose in training procedure. Training images with frontal faces were taken with professional camera and lightning. Training images are similar to those used in identification documents. System solved problem know as one sample per person problem. A new recognition system is represented. System first does localization of eye pupil center. Using centers of both eye pupils system does the geometric normalization. Local light normalization is then applied on geometrically normalized images. Comparison of different light normalization techniques is represented. The performed experiments show better behavior of gradient faces as light normalization technique. It has also been demonstrated that KPCA recognition method is more suitable in recognition performed on video clips that simulate real situations.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:589348
Study programmeTitle: Postgraduate master programe in computing
Study programme type: university
Study level: postgraduate
Academic / professional title: magistar inženjer računarstva (magistar inženjer računarstva)
Catalog URLhttp://lib.fer.hr/cgi-bin/koha/opac-detail.pl?biblionumber=36997
Type of resourceText
Extent95 str ; 30 cm
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Created on2020-08-26 08:11:19