LiDAR Point Cloud 3D Attribute Extraction and Development of PCL Based Visualization Interface

Teh Peh Chiong*, Lai Koon Chun **, Adrian Teo Wei Hong ***, Ng Kok Leong ****, Ong Chu En *****
* Assistant Professor, Department of Electronic Engineering, Universiti Tunku Abdul Rahman, Malaysia.
** Assistant Professor in the Department of PetroChemical Engineering, Universiti Tunku Abdul Rahman, Malaysia.
*** Engineer, Universiti Tunku Abdul Rahman, Malaysia
****_***** Research Assistant, Universiti Tunku Abdul Rahman, Malaysia.
Periodicity:July - December'2017


Handling LiDAR data have been growing ever since the high demand in automotive vehicle and surveillance system application. This paper introduces a conversion tool which allows the extraction of point cloud data while rearranging the data to fit Point Cloud Library (PCL) input format which is known as point cloud data (PCD). Scanse Sweep LiDAR is used as an initial guidance in LiDAR data acquisition where it is able to export .csv and .xyz data. Conversion such as cartesian to polar have also been included due to Scanse Sweep hardware .csv format is arranged in polar form. Moreover, converted point cloud is processed using PCL greedy fast triangulation method for 3D modelling and random sample consensus (RANSAC) algorithm used for plane segmentation which each features are combined in a single application constructed using LabVIEW.


LiDAR, Point Cloud Library, Scanse Sweep, RANSAC, PCD Format

How to Cite this Article?

Chiong, T. P., Leong, N. K., En, O. C., Chun, L. K., and Hong, A. T. W. (2017). LiDAR Point Cloud 3D attribute extraction and development of PCL based visualization interface. i-manager's Journal on Cloud Computing, 4(2), 15-22.


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