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Title:Zaznavanje obrazov v video vsebinah in njihova klasifikacija
Authors:ID Močnik, Grega (Author)
ID Kačič, Zdravko (Mentor) More about this mentor... New window
ID Zimšek, Danilo (Comentor)
Files:.pdf MAG_Mocnik_Grega_2017.pdf (2,32 MB)
MD5: DAB5704234CD6411CE91B76F2A45CE72
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Namen magistrskega dela je razviti sistem, ki zna učinkovito zaznati obraz v video vsebinah. Izdelali smo sistem, ki zazna obraz in ga klasificira za nadaljnjo obravnavo v drugih sistemih. Razložili smo proces zaznave in prepoznave obraza, napisali kratek pregled tehnologij in algoritmov, ki se uporabljajo danes. Predstavili smo princip zaznave obraza v video vsebinah, ki je neodvisen od vira video vsebine. Uporabljeni metodi za zaznavo obrazov sta analiza glavnih komponent in razvrščanje značilk s Haarovimi razvrščevalniki. Pri izvedbi sistema zaznave obrazov v video vsebinah smo uporabili funkcije iz knjižnice OpenCV. Sistem je bil razvit v programskem jeziku Python, saj smo želeli ustvariti sistem, ki je med drugim tudi prenosljiv med platformami. Sistem se je med testiranjem izkazal za učinkovitega, z določenimi izboljšavami pa bo koristna osnova za nadaljnjo procesiranje in prepoznavo obrazov.
Keywords:zaznavanje obraza, prepoznava obraza, analiza glavnih komponent, Haarov klasifikator, video
Place of publishing:[Maribor
Publisher:G. Močnik
Year of publishing:2017
PID:20.500.12556/DKUM-65736 New window
UDC:004.93'1(043.2)
COBISS.SI-ID:20624150 New window
NUK URN:URN:SI:UM:DK:BWYU0JEQ
Publication date in DKUM:25.05.2017
Views:1921
Downloads:266
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
MOČNIK, Grega, 2017, Zaznavanje obrazov v video vsebinah in njihova klasifikacija [online]. Master’s thesis. Maribor : G. Močnik. [Accessed 22 January 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=65736
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Secondary language

Language:English
Title:Detection of faces in video content and their classification
Abstract:The purpose of the master thesis is to develop a system that is able to effectively detect a face in a video content. We developed a system that detects a face and classifies it for further processing in other systems. We explained the process of perception and facial recognition, wrote a brief overview of technologies and algorithms we use today. We presented the principle of Face Detection in video content that is independent of the video content stream. Used methods for face detection are principal component analysis and classification with Haar cascade classifiers. To create the system for face detection, we used the functions from the OpenCV library. The system was developed in the Python programming language, as we wanted to create a system that is portable between platforms. The experimental results showed that the developed system is efficient and with certain improvements it will be a useful basis for further processing and face recognition.
Keywords:face detection, face recognition, principal component analysis, Haar classifier, video


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