magistrsko delo
Emin Pamuk (Author), Damjan Vlaj (Mentor), Gregor Močnik (Co-mentor), Jernej Rošker (Co-mentor)

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;magistrske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: [E. Pamuk]
UDC: 004.93.032.26(043.2)
COBISS: 152729091 Link will open in a new window
Views: 108
Downloads: 32
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Other data

Secondary language: English
Secondary title: Development of a system for automatic tracking of dynamic regions of interest and determination of gaze orientation
Secondary 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.
Secondary keywords: semantic segmentation;neural network;gaze tracking;
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Elektrotehnika
Pages: 1 spletni vir (1 datoteka PDF (XI, 83 f.))
ID: 18418181