Depth estimation from 3D reconstructed scene using stereo vision

In the past few years, a growing interest in mobile robot’s applications produce a persistent need to develop assistive systems that can help those robots to do their job efficiently. Distance estimation is one of these applications that a lot of researches made to develop it. Visionary sensors such...

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Main Author:	Omer Ba-saleem, Omer Mohamed
Format:	Thesis
Language:	English English
Published:	2018
Subjects:	TA1501-1820 Applied optics Photonics
Online Access:	http://eprints.uthm.edu.my/192/1/24p%20OMER%20MOHAMED%20OMER%20BA-SALEEM.pdf http://eprints.uthm.edu.my/192/2/OMER%20MOHAMED%20OMER%20BA-SALEEM%20WATERMARK.pdf
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id	my-uthm-ep.192
record_format	uketd_dc
spelling	my-uthm-ep.1922021-06-22T01:40:22Z Depth estimation from 3D reconstructed scene using stereo vision 2018-01 Omer Ba-saleem, Omer Mohamed TA1501-1820 Applied optics. Photonics In the past few years, a growing interest in mobile robot’s applications produce a persistent need to develop assistive systems that can help those robots to do their job efficiently. Distance estimation is one of these applications that a lot of researches made to develop it. Visionary sensors such as stereo vision optimization method is one of the most efficient methods among traditional sensors that have been used to estimate a depth from 3D reconstructed scene. Vision sensor can be used in rescue robots mission instead of human providing a way to estimate the distance between the robot camera and the objects in front it and give a 3D model of that obstacle which can help rescuers. Although vision sensors have some disadvantages such as the change of illumination of the captured images and the change in the background. In this project, the objectives are developing a stereo vision system to extract depth from 3D reconstructed scene, analyse the performance of the proposed stereo vision system and develop a graphical user interface (GUI) to monitor the performance of the stereo vision system. Two low-cost cameras have been used to works as stereo camera sensor. Stereo camera parameters from the camera calibration process and disparity map by using the block matching in order to collect the corresponding pixels between both stereo images are important parameters to estimate the depth from the 3D reconstructed scene. The experiment results have been done by testing an object far from the stereo camera by 1.0 and 1.5 meters and the experiment conducted at indoor and outdoor environments. The results show that the mean error of depth increasers with increasing distance to the stereo camera. In addition, the quality of the texture of the 3D virtual model also decreased with the increasing of the distance. The camera mean accuracy reaches to 90.14%. Finally, using stereo vision in order to estimate depth from the scene have been done and it can be use at rescue missions to help at rescue’s robots missions. 2018-01 Thesis http://eprints.uthm.edu.my/192/ http://eprints.uthm.edu.my/192/1/24p%20OMER%20MOHAMED%20OMER%20BA-SALEEM.pdf text en public http://eprints.uthm.edu.my/192/2/OMER%20MOHAMED%20OMER%20BA-SALEEM%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English
topic	TA1501-1820 Applied optics Photonics
spellingShingle	TA1501-1820 Applied optics Photonics Omer Ba-saleem, Omer Mohamed Depth estimation from 3D reconstructed scene using stereo vision
description	In the past few years, a growing interest in mobile robot’s applications produce a persistent need to develop assistive systems that can help those robots to do their job efficiently. Distance estimation is one of these applications that a lot of researches made to develop it. Visionary sensors such as stereo vision optimization method is one of the most efficient methods among traditional sensors that have been used to estimate a depth from 3D reconstructed scene. Vision sensor can be used in rescue robots mission instead of human providing a way to estimate the distance between the robot camera and the objects in front it and give a 3D model of that obstacle which can help rescuers. Although vision sensors have some disadvantages such as the change of illumination of the captured images and the change in the background. In this project, the objectives are developing a stereo vision system to extract depth from 3D reconstructed scene, analyse the performance of the proposed stereo vision system and develop a graphical user interface (GUI) to monitor the performance of the stereo vision system. Two low-cost cameras have been used to works as stereo camera sensor. Stereo camera parameters from the camera calibration process and disparity map by using the block matching in order to collect the corresponding pixels between both stereo images are important parameters to estimate the depth from the 3D reconstructed scene. The experiment results have been done by testing an object far from the stereo camera by 1.0 and 1.5 meters and the experiment conducted at indoor and outdoor environments. The results show that the mean error of depth increasers with increasing distance to the stereo camera. In addition, the quality of the texture of the 3D virtual model also decreased with the increasing of the distance. The camera mean accuracy reaches to 90.14%. Finally, using stereo vision in order to estimate depth from the scene have been done and it can be use at rescue missions to help at rescue’s robots missions.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Omer Ba-saleem, Omer Mohamed
author_facet	Omer Ba-saleem, Omer Mohamed
author_sort	Omer Ba-saleem, Omer Mohamed
title	Depth estimation from 3D reconstructed scene using stereo vision
title_short	Depth estimation from 3D reconstructed scene using stereo vision
title_full	Depth estimation from 3D reconstructed scene using stereo vision
title_fullStr	Depth estimation from 3D reconstructed scene using stereo vision
title_full_unstemmed	Depth estimation from 3D reconstructed scene using stereo vision
title_sort	depth estimation from 3d reconstructed scene using stereo vision
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Faculty of Electrical and Electronic Engineering
publishDate	2018
url	http://eprints.uthm.edu.my/192/1/24p%20OMER%20MOHAMED%20OMER%20BA-SALEEM.pdf http://eprints.uthm.edu.my/192/2/OMER%20MOHAMED%20OMER%20BA-SALEEM%20WATERMARK.pdf
_version_	1747830550340567040

Depth estimation from 3D reconstructed scene using stereo vision

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