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Title:
Primerjava postopkov za prepoznavanje oseb v nekontroliranem okolju : diplomsko delo
Authors:
ID
Oblak, Žan
(Author)
ID
Potočnik, Božidar
(Mentor)
More about this mentor...
Files:
VS_Oblak_Zan_2021.pdf
(1,61 MB)
MD5: A60ECD9D4ED8FB6DC49355AD9CFFF43C
PID:
20.500.12556/dkum/855efb82-2d64-4419-bef0-0bffbefd1a34
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
V diplomskem delu smo se ukvarjali z analizo metod za prepoznavanje oseb v nekontroliranem okolju. Cilj naše raziskave je bil preštudirati in primerjati različne metode, nato pa na osnovi postavljenih kriterijev izbrati najprimernejšo za različne vrste aplikacij. Najprej smo opravili pregled področja ter identificirali obstoječe odprtokodne metode. Zatem smo preučili metrike za merjenje zmogljivosti postopkov za prepoznavo oseb v nekontroliranem okolju. Po opravljenem študiju smo izbrali tri metode za testiranje, in sicer metodo Ageitgey/face_recognition, SphereFace ter OpenBR. Za namen testiranja smo preučili in namestili javni podatkovni zbirki LFW in UTKFace, ki vsebujeta osebe v nekontroliranem okolju. V eksperimentalnem delu smo testirali posamezno metodo s pomočjo eksperimentalnih podatkovnih zbirk. Testiranje smo izvajali na prenosnem računalniškem sistemu, pri čemer smo beležili število pozitivnih in negativnih detekcij. Z dobljenimi rezultati smo nato izračunali šest uveljavljenih metrik na področju prepoznavanja oseb v nekontroliranem okolju, opazovali pa smo tudi procesorsko in prostorsko zahtevnost metod. Najslabše se je odrezala metoda Ageitgey/face_recognition, najbolje pa metoda SphereFace. Metoda OpenBR je bila na zbirki LFW celo enakovredna metodi SphereFace. Na osnovi eksperimentiranj zaključujemo, da je za uporabo v domačem okolju najbolje uporabiti metodo Ageitgey/face_recognition. Za uporabo v profesionalnem okolju pa se odločimo med metodama SphereFace in OpenBR, in sicer glede na sistemske vire, ki jih imamo na razpolago.
Keywords:
prepoznava oseb
,
nekontrolirano okolje
,
primerjava metod
,
računalniški vid
Place of publishing:
Maribor
Place of performance:
Maribor
Publisher:
[Ž. Oblak]
Year of publishing:
2021
Number of pages:
X, 46 f.
PID:
20.500.12556/DKUM-80232
UDC:
004.932.72(043.2)
COBISS.SI-ID:
90520579
Publication date in DKUM:
18.10.2021
Views:
818
Downloads:
48
Metadata:
Categories:
KTFMB - FERI
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OBLAK, Žan, 2021,
Primerjava postopkov za prepoznavanje oseb v nekontroliranem okolju : diplomsko delo
[online]. Bachelor’s thesis. Maribor : Ž. Oblak. [Accessed 22 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=80232
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
02.09.2021
Secondary language
Language:
English
Title:
Comparison of procedures for person recognition in an uncontrolled environment
Abstract:
In the bachelor's thesis we dealt with the analysis of methods for recognizing persons in an uncontrolled environment. The aim of our research was to study and compare different methods, and then, based on the set criteria, select the most suitable for different types of applications. We first reviewed the field and identified existing open source methods. We then examined metrics to measure performance of procedures for identifying persons in an uncontrolled environment. After the study, we selected three procedures for testing, namely the Ageitgey/face_recognition, SphereFace and OpenBR procedures. For testing purposes, we examined and installed public databases LFW and UTKFace that contain individuals in an uncontrolled environment. In the experimental part, we tested individual procedures with the help of experimental databases. Testing was performed on a portable computer system, recording the number of positive and negative results. With the obtained results, we then calculated six established metrics in the field of recognizing persons in an uncontrolled environment. Processor and spatial complexity of procedures were also observed. Ageitgey/face_recognition performed the worst, and SphereFace performed the best. OpenBR on the LFW database was even equivalent to SphereFace. Based on the experiments, we conclude that it is best to use Ageitgey/face_recognition for use in the home environment. For use in a professional environment, we choose between OpenBR and SphereFace, depending on the system resources we have at our disposal.
Keywords:
person recognition
,
uncontrolled environment
,
method comparison
,
computer vision.
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