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FRANSAC: Fast RANdom Sample Consensus for 3D Plane Segmentation

by Ramy Ashraf Zeineldin, Nawal Ahmed El-Fishawy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 167 - Number 13
Year of Publication: 2017
Authors: Ramy Ashraf Zeineldin, Nawal Ahmed El-Fishawy
10.5120/ijca2017914558

Ramy Ashraf Zeineldin, Nawal Ahmed El-Fishawy . FRANSAC: Fast RANdom Sample Consensus for 3D Plane Segmentation. International Journal of Computer Applications. 167, 13 ( Jun 2017), 30-36. DOI=10.5120/ijca2017914558

@article{ 10.5120/ijca2017914558,
author = { Ramy Ashraf Zeineldin, Nawal Ahmed El-Fishawy },
title = { FRANSAC: Fast RANdom Sample Consensus for 3D Plane Segmentation },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 167 },
number = { 13 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 30-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume167/number13/27832-2017914558/ },
doi = { 10.5120/ijca2017914558 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:14:46.235484+05:30
%A Ramy Ashraf Zeineldin
%A Nawal Ahmed El-Fishawy
%T FRANSAC: Fast RANdom Sample Consensus for 3D Plane Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 167
%N 13
%P 30-36
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Scene analysis is a prior stage in many computer vision and robotics applications. Thanks to recent depth camera, we propose a fast plane segmentation approach for obstacle detection in indoor environments. The proposed method Fast RANdom Sample Consensus (FRANSAC) involves three steps: data input, data preprocessing and 3D RANSAC. Firstly, range data, obtained from 3D camera, is converted into 3D point clouds. Next, a preprocessing stage is introduced where a pass through and voxel grid filters are applied. Finally, planes are estimated using a modified 3D RANSAC. The experimental results demonstrate that our approach can segment planes and detect obstacles about 7 times faster than the standard RANSAC without losing the discriminative power.

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Index Terms

Computer Science
Information Sciences

Keywords

RANSAC point cloud plane segmentation Kinect RGB-D Voxel