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FRANSAC: Fast RANdom Sample Consensus for 3D Plane Segmentation
| 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
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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