segmentation Tutorials
=========================


Plane model segmentation
~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial, we will learn how to segment arbitrary plane models from a given point cloud dataset.

* `Original <http://pointclouds.org/documentation/tutorials/planar_segmentation.php#planar-segmentation>`_ \
* TestCode : examples/official/Segmentation/Plane_model_segmentation.py


Cylinder model segmentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial, we will learn how to segment arbitrary cylindrical models from a given point cloud dataset.

* `Original <http://pointclouds.org/documentation/tutorials/cylinder_segmentation.php#cylinder-segmentation>`_ \
* TestCode : examples/official/Segmentation/cylinder_segmentation.py


Euclidean Cluster Extraction
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial we will learn how to extract Euclidean clusters with the pcl::EuclideanClusterExtraction class.

* `Original <http://pointclouds.org/documentation/tutorials/cluster_extraction.php#cluster-extraction>`_ \
* TestCode : examples/official/Segmentation/cluster_extraction.py


Region growing segmentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial we will learn how to use region growing segmentation algorithm.

* `Original <http://pointclouds.org/documentation/tutorials/region_growing_segmentation.php#region-growing-segmentation>`_ \
* TestCode : None


Color-based region growing segmentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial we will learn how to use color-based region growing segmentation algorithm.

* `Original <http://pointclouds.org/documentation/tutorials/region_growing_rgb_segmentation.php#region-growing-rgb-segmentation>`_ \
* TestCode : None


Min-Cut Based Segmentation
~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial we will learn how to use min-cut based segmentation algorithm.

* `Original <http://pointclouds.org/documentation/tutorials/min_cut_segmentation.php#min-cut-segmentation>`_ \
* TestCode : None


Conditional Euclidean Clustering
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This tutorial describes how to use the Conditional Euclidean Clustering class in PCL: A segmentation algorithm that clusters points based on Euclidean distance and a user-customizable condition that needs to hold.

* `Original <http://pointclouds.org/documentation/tutorials/conditional_euclidean_clustering.php#conditional-euclidean-clustering>`_ \
* TestCode : None


Difference of Normals Based Segmentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial we will learn how to use the difference of normals feature for segmentation.

* `Original <http://pointclouds.org/documentation/tutorials/don_segmentation.php#don-segmentation>`_ \
* TestCode : None


Clustering of Pointclouds into Supervoxels - Theoretical primer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial, we show to break a pointcloud into the mid-level supervoxel representation.

* `Original <http://pointclouds.org/documentation/tutorials/supervoxel_clustering.php#supervoxel-clustering>`_ \
* TestCode : None


Identifying ground returns using ProgressiveMorphologicalFilter segmentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial, we show how to segment a point cloud into ground and non-ground returns.

* `Original <http://pointclouds.org/documentation/tutorials/progressive_morphological_filtering.php#progressive-morphological-filtering>`_ \
* TestCode : None


Filtering a PointCloud using ModelOutlierRemoval
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This tutorial describes how to extract points from a point cloud using SAC models

* `Original <http://pointclouds.org/documentation/tutorials/model_outlier_removal.php#model-outlier-removal>`_ \
* TestCode : None


