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Prepoznava obrazov z opisnikom Alfa-Gama
ID
Lušina, Domen
(
Author
),
ID
Kristan, Matej
(
Mentor
)
More about this mentor...
,
ID
Maver, Jasna
(
Comentor
)
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MD5: 44E9E8C08D66876BFF5DD07CCC88E499
PID:
20.500.12556/rul/5ce398f3-8132-4cd4-be3f-238efa46a62a
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Abstract
Za prepoznavo obrazov obstajajo številne metode, nekatere med njimi za prepoznavo uporabljajo lokalne opisnike. V tej diplomskem delu si bomo za namen prepoznave obrazov ogledali delovanje popolnoma novega lokalnega opisnika, imenovanega Alfa-Gama (krajše AG), ki je bil razvit v Laboratoriju za vizualne in spoznavne sisteme na Fakulteti za računalništvo in informatiko v Ljubljani. Pripravili smo sistem za prepoznavo obrazov na podlagi algoritma vreče besed in klasifikatorja SVM . Predlagan sistem smo razvili za številne popularne opisnike in opisnik AG. Sistem smo testirali na javno dostopnih podatkovnih bazah. V večini primerov je opisnik AG izboljšal rezultate prepoznave in se je izkazal za dobro alternativo k ostalim testiranim opisnikom.
Language:
Slovenian
Keywords:
Alfa-Gama opisnik
,
računalniški vid
,
prepoznava obraza
,
detekcija obraza
,
lokalni opisniki
Work type:
Bachelor thesis/paper
Organization:
FRI - Faculty of Computer and Information Science
Year:
2017
PID:
20.500.12556/RUL-95926
Publication date in RUL:
25.09.2017
Views:
2755
Downloads:
299
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LUŠINA, Domen, 2017,
Prepoznava obrazov z opisnikom Alfa-Gama
[online]. Bachelor’s thesis. [Accessed 29 March 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=95926
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Language:
English
Title:
Face recognition using Alapha-Gamma descriptor
Abstract:
For facial recognition there are numerous methods available, some of them use local descriptors. In this thesis, for the purpose of face recognition, we will take a closer look at novel local descriptor Alpha-Gamma (shorter AG) developed at the Visual Cognitive Systems Laboratory at the Faculty Of Computer and Information Science, University of Ljubljana. We developed a system for face recognition using bag of words algorithm and SVM classifier. The proposed system was developed for several popular local descriptors and AG. We used publicly available databases for testing. In most cases AG improved facial recognition rate and was shown as a good alternative to other tested local descriptors.
Keywords:
Alpha-Gamma descriptor
,
computer vision
,
facial recognition
,
face detection
,
local descriptors
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