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Title:Razvoj sistema za avtomatsko sledenje dinamičnih območij interesa in določanje usmerjenosti pogleda : magistrsko delo
Authors:ID Pamuk, Emin (Author)
ID Vlaj, Damjan (Mentor) More about this mentor... New window
ID Močnik, Grega (Comentor)
ID Rošker, Jernej (Comentor)
Files:.pdf MAG_Pamuk_Emin_2023.pdf (4,63 MB)
MD5: CC59898A6D92238C78E07E5477D064F6
 
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 magistrske naloge je bil razviti sistem, ki analizira podatke pridobljene s pomočjo sledilnika pogleda in definira dinamično področje zanimanja na video posnetku. Področje zanimanja predstavlja oseba, ki se ji določijo referenčne točke na ključni delih telesa. V ta namen smo uporabili dve metodi za zaznavanje področja zanimanja in določanje ključnih točk, ki temeljita na nevronskih mrežah. Za implementacijo smo uporabili funkcije iz knjižnice OpenCV, sistem pa je bil razvit v programskem jeziku Python. Razviti sistem se je izkazal kot učinkovit za prepoznavanje področij interesa in je omogočil visoko ujemanje s kvalitativnim kodiranjem eksperta.
Keywords:semantična segmentacija, nevronske mreže, sledenje pogleda
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[E. Pamuk]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF (XI, 83 f.))
PID:20.500.12556/DKUM-84019 New window
UDC:004.93.032.26(043.2)
COBISS.SI-ID:152729091 New window
Publication date in DKUM:13.04.2023
Views:631
Downloads:90
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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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:29.03.2023

Secondary language

Language:English
Title:Development of a system for automatic tracking of dynamic regions of interest and determination of gaze orientation
Abstract:The master thesis aim is the development of the system that analyses the data obtained by a view tracker and defines a dynamic region of interest in a video. The region of interest is represented by a person to whom reference points are assigned on key body parts. For this purpose, two methods for detecting the region of interest and defining the key points used are based on neural networks. Functions from the OpenCV library are used for the implementation, and the system is developed in the Python programming language. The developed system proved to be effective for identifying areas of interest and allowed high agreement with the qualitative coding of the expert.
Keywords:semantic segmentation, neural network, gaze tracking


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