upsamplingCloudPCL

Upsampling method for an input cloud using MovingLeastSquares method of PCL

Input file structure support

Format	Description
.pcd	Point Cloud Data file format
.ply	Polygon file format
.txt	Text file format
.xyz	X Y Z Text file format

Output file structure (.pcd)

• unsampled_cloud.pcd

Example

Command line

Usage: ./upsampling_cloud [options] 

Optional arguments:
-h --help         	shows help message and exits [default: false]
-v --version      	prints version information and exits [default: false]
--cloudfile       	input cloud file [required]
--search-radius   	search radius value [default: 0.03]
--sampling-radius 	sampling radius value [default: 0.005]
--step-size       	step size [default: 0.005]
-o --output-dir   	output dir to save upsampled cloud [default: "-"] (not configured)
-d --display      	display upsampling in the pcl visualizer [default: false]

Dependencies

This projects depends on the Point Cloud Library (it works with version 1.8...1.12.1) and its dependencies.

Package	Version	Description
VTK	9.0.0	Visualization toolkit
PCL	1.12.1	The Point Cloud Library (PCL)
Eigen	3.7.7	Eigen is a library of template headers for linear algebra
Flann	1.9.1	Fast Library for Approximate Nearest Neighbors
Boost	1.77.0	Provides support for linear algebra, pseudorandom number generation, multithreading
OpenGL	21.2.6	Programming interface for rendering 2D and 3D vector graphics.

Compilation

Compile from source

1. Download source code

git clone https://github.com/danielTobon43/upsamplingCloudPCL

2. Create a "build" folder at the top level of the upsamplingCloudPCL

cd upsamplingCloudPCL/ && mkdir build

3. Compile with CMake

cd build/ && cmake ../ && make

Test

cd /build
./upsampling_cloud --cloudfile <path/to/cloud-file>

Note

You can modify the parameters to obtain better results here

mls.setComputeNormals(true);
mls.setInputCloud(input_cloud);
mls.setSearchMethod(kd_tree);
mls.setSearchRadius(search_radius);
mls.setUpsamplingMethod(pcl::MovingLeastSquares<pcl::PointXYZRGB, pcl::PointXYZRGB>::UpsamplingMethod::SAMPLE_LOCAL_PLANE);
mls.setUpsamplingRadius(sampling_radius);
mls.setUpsamplingStepSize(step_size);
mls.setPolynomialOrder(pol_order);
mls.setSqrGaussParam(gauss_param);// (the square of the search radius works best in general)
mls.setCacheMLSResults(true);//Set whether the mls results should be stored for each point in the input cloud.
mls.setNumberOfThreads(num_threats);