Uporaba umetne inteligence za preslikavo človeškega gibanja v 3D modele : magistrsko delo

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Title:	Uporaba umetne inteligence za preslikavo človeškega gibanja v 3D modele : magistrsko delo
Authors:	ID Stopar, Primož (Author) ID Zorman, Milan (Mentor) More about this mentor... ID Tomažič, Blaž (Comentor)
Files:	MAG_Stopar_Primoz_2022.pdf (3,82 MB) MD5: 0F6046A377C0A2E8208317504E2D38C4 PID: 20.500.12556/dkum/be3426dd-5c10-4a46-85b2-ef8f96bef271
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	V magistrskem delu smo predstavili uporabo umetne inteligence za preslikavo človeškega gibanja v trodimenzionalni model na mobilnih napravah. Predstavili smo različne načine delovanja modelov umetne inteligence za ocenitev poze. Opisali smo nekaj že naučenih modelov umetne inteligence in ogrodij, s katerimi lahko modele umetne inteligence vključimo v igralni pogon Unity. Rešitev smo implementirali v pogonu Unity z ogrodjem MediaPipe in družino modelov umetne inteligence BlazePose. Ugotovili smo, da lahko že na povprečnih mobilnih napravah dosežemo skoraj realno časovno izvajanje. Prav tako menimo, da tehnologija še ni primerna za uporabo v zdravstvene namene, je pa primerna za uporabo v aplikacijah, namenjenih zabavi.
Keywords:	MediaPipe, BlazePose, ocenitev poze, sledenje pozam, konvolucijske nevronske mreže
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[P. Stopar]
Year of publishing:	2022
Number of pages:	1 spletni vir (1 datoteka PDF (X, 82 f.))
PID:	20.500.12556/DKUM-81997
UDC:	004.8:004.932(043.2)
COBISS.SI-ID:	116087043
Publication date in DKUM:	08.07.2022
Views:	796
Downloads:	156
Metadata:
Categories:	KTFMB - FERI
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Licences

License:	CC BY 4.0, Creative Commons Attribution 4.0 International

Link:	http://creativecommons.org/licenses/by/4.0/
Description:	This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:	27.06.2022

Secondary language

Language:	English
Title:	Using artificial intelligence for mapping human motion into 3D models
Abstract:	In the thesis we presented the use of artificial intelligence, to map human movement into three dimensional models on mobile devices. We have presented different designs of artificial intelligence models for pose estimation. We have described some already learned models of artificial intelligence and framework with which we can include models to the Unity engine. We implemented the solution in Unity engine, using MediaPipe framework and group of BlazePose models. We found out that we can achieve almost real-time performance on average mobile devices. We also believe that the technology is not yet suitable for use in medical purposes, but it can be used in applications intended for entertainment.
Keywords:	MediaPipe, BlazePose, pose estimation, pose tracking, convolutional neural network

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