Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm

Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm

A 3D reconstruction using stereo cameras still becomes an issue among researchers specialized in computer vision. The corresponding pixel between two images from stereo camera needs to be estimated accurately. One of the widely used methods is Semi-Global Matching (SGM), which uses mutual informatio...

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Main Authors: Achmad, M. S. Hendriyawan, Findari, Widya Setia, Nurnajmin Qasrina, Ann, Pebrianti, Dwi, Mohd Razali, Daud
Format: Conference or Workshop Item
Language:English
Published: IEEE 2016
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/18253/
http://umpir.ump.edu.my/id/eprint/18253/
http://umpir.ump.edu.my/id/eprint/18253/2/Stereo%20camera%20-%20Based%203D%20object%20reconstruction%20utilizing%20Semi-Global%20Matching%20Algorithm%201.pdf
id ump-18253
recordtype eprints
spelling ump-182532018-05-16T06:01:30Z http://umpir.ump.edu.my/id/eprint/18253/ Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm Achmad, M. S. Hendriyawan Findari, Widya Setia Nurnajmin Qasrina, Ann Pebrianti, Dwi Mohd Razali, Daud TK Electrical engineering. Electronics Nuclear engineering A 3D reconstruction using stereo cameras still becomes an issue among researchers specialized in computer vision. The corresponding pixel between two images from stereo camera needs to be estimated accurately. One of the widely used methods is Semi-Global Matching (SGM), which uses mutual information (MI) in the form of entropy between two pixels to determine the level of similarity based on the smallest energy (lower cost). The reconstruction result shows the percentage of registered pointcloud is equal to 62.11% where the observation distance ranges are between 1 to 4 meters. In this research, a nearest-neighbor filter is utilized to improve the pointcloud quality where the variations of the neighbor's number are 4 to 128 pixels. The results show that this technique can eliminate the outliers up to 4.9% with the standard deviation of nearest-neighbor distances means equals to 1.0. IEEE 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/18253/2/Stereo%20camera%20-%20Based%203D%20object%20reconstruction%20utilizing%20Semi-Global%20Matching%20Algorithm%201.pdf Achmad, M. S. Hendriyawan and Findari, Widya Setia and Nurnajmin Qasrina, Ann and Pebrianti, Dwi and Mohd Razali, Daud (2016) Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm. In: International Conference on Science and Technology-Computer (ICST), 27-28 October 2016 , Yogyakarta, Indonesia. pp. 1-6.. ISBN 978-1-5090-4357-6 https://doi.org/10.1109/ICSTC.2016.7877373
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Achmad, M. S. Hendriyawan
Findari, Widya Setia
Nurnajmin Qasrina, Ann
Pebrianti, Dwi
Mohd Razali, Daud
Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm
description A 3D reconstruction using stereo cameras still becomes an issue among researchers specialized in computer vision. The corresponding pixel between two images from stereo camera needs to be estimated accurately. One of the widely used methods is Semi-Global Matching (SGM), which uses mutual information (MI) in the form of entropy between two pixels to determine the level of similarity based on the smallest energy (lower cost). The reconstruction result shows the percentage of registered pointcloud is equal to 62.11% where the observation distance ranges are between 1 to 4 meters. In this research, a nearest-neighbor filter is utilized to improve the pointcloud quality where the variations of the neighbor's number are 4 to 128 pixels. The results show that this technique can eliminate the outliers up to 4.9% with the standard deviation of nearest-neighbor distances means equals to 1.0.
format Conference or Workshop Item
author Achmad, M. S. Hendriyawan
Findari, Widya Setia
Nurnajmin Qasrina, Ann
Pebrianti, Dwi
Mohd Razali, Daud
author_facet Achmad, M. S. Hendriyawan
Findari, Widya Setia
Nurnajmin Qasrina, Ann
Pebrianti, Dwi
Mohd Razali, Daud
author_sort Achmad, M. S. Hendriyawan
title Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm
title_short Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm
title_full Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm
title_fullStr Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm
title_full_unstemmed Stereo Camera - Based 3D Object Reconstruction Utilizing Semi-Global Matching Algorithm
title_sort stereo camera - based 3d object reconstruction utilizing semi-global matching algorithm
publisher IEEE
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/18253/
http://umpir.ump.edu.my/id/eprint/18253/
http://umpir.ump.edu.my/id/eprint/18253/2/Stereo%20camera%20-%20Based%203D%20object%20reconstruction%20utilizing%20Semi-Global%20Matching%20Algorithm%201.pdf
first_indexed 2023-09-18T22:25:45Z
last_indexed 2023-09-18T22:25:45Z
_version_ 1777415954549964800

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