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master's thesis
Tenzorske metode u prepoznavanju lica
Zagreb: University of Zagreb, Faculty of Science, 2018. urn:nbn:hr:217:774106
Poštić, Suraja
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

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Poštić, S. (2018). Tenzorske metode u prepoznavanju lica (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:774106

Poštić, Suraja. "Tenzorske metode u prepoznavanju lica." Master's thesis, University of Zagreb, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:217:774106

Poštić, Suraja. "Tenzorske metode u prepoznavanju lica." Master's thesis, University of Zagreb, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:217:774106

Poštić, S. (2018). 'Tenzorske metode u prepoznavanju lica', Master's thesis, University of Zagreb, Faculty of Science, accessed 23 November 2024, https://urn.nsk.hr/urn:nbn:hr:217:774106

Poštić S. Tenzorske metode u prepoznavanju lica [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2018 [cited 2024 November 23] Available at: https://urn.nsk.hr/urn:nbn:hr:217:774106

S. Poštić, "Tenzorske metode u prepoznavanju lica", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:217:774106

Metadata
TitleTenzorske metode u prepoznavanju lica
AuthorSuraja Poštić
MentorZlatko Drmač (mentor)
Committee memberZlatko Drmač (predsjednik povjerenstva)
Committee memberZoran Vondraček (član povjerenstva)
Committee memberSlaven Kožić (član povjerenstva)
Committee memberSonja Štimac (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2018-09-24, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Rad opisuje algoritam za prepoznavanje lica temeljen na tenzorima. Višedimenzionalna algebra omogućila nam je da uzmemo u obzir raznolike uvjete u kojima osoba može biti uslikana. Razlikovali smo izraze lica, osvjetljenja i kuteve gledišta. Prepoznavanje nepoznatog izraza lica obavljeno je vrlo uspješno. Suočavanjem algoritma s drugačijim osvjetljenjem ili kutem gledišta točnost klasifikacije značajno se smanjila. Redukcijom dimenzije osvjetljenja ublažili smo izražene svjetlosne kontraste. Posjedujemo li bazu slika s velikim brojem različitih osvjetljenja ovaj postupak možemo provesti prije same klasifikacije. Time izbjegavamo nebitne razlike među slikama iste osobe. Isto vrijedi i za ostale dimenzije u kojima je aproksimacija nižim rangom logična.
Abstract (english)
This thesis describes tensor based algorithm for face recognition. Multilinear algebra enabled us to take into consideration various scene conditions usually found in images. We distinguish face expressions, illumination and view points. Recognition of unfamiliar face expression was very successful. Facing with different illumination or viewpoint resulted in a significant accuracy drop. Reducing the dimension related to illumination we have managed to smooth noticeable light contrasts. In case we posses image base with many different illumination conditions we can conduct this procedure prior to the classification process. As a result we avoid inessential differences between images of the same person. Same applies to another dimension where dimensionality reduction makes sense.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:774106
Study programmeTitle: Finance and Business Mathematics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-06-12 11:19:05