Point Cloud outlier removal

Name: “point_cloud_outlier_removal”

Description

Point cloud outlier removal

Configuration

Name	Description	Type	Available value	Default value	Required
method	Method for point cloud outlier removal	string	“statistical”, “small_components”	“statistical”	No
save_intermediate_data	Save points clouds as laz and csv format	boolean		false	No

If method is statistical:

Name	Type	Available value	Default value	Required
k	int	should be > 0	50	No
filtering_constant	float	should be >= 0	0	No
mean_factor	float	should be >= 0	1.3	No
std_dev_factor	float	should be >= 0	3.0	No
use_median	bool		True	No
half_epipolar_size	int		5	No

If method is small_components

Name	Type	Default value	Required
on_ground_margin	int	11	No
connection_distance [1]	float	None [1]	No
nb_points_threshold	int	50	No
clusters_distance_threshold	float	None	No
half_epipolar_size	int	5	No

Warning

There is a particular case with the Point Cloud outlier removal application because both methods can be used at the same time in the pipeline. The ninth step consists of Filter the 3D points cloud via N consecutive filters. So you can configure the application any number of times. By default the filtering is done twice : once with the small_components, once with the statistical filter. To use your own filters in the order you want, you can add an identifier at the end of each application key :

point_cloud_outlier_removal.my_first_filter
point_cloud_outlier_removal.filter_2
point_cloud_outlier_removal.3

The filtering steps will then be executed in the order you provided them.

Because by default the applications point_cloud_outlier_removal.1 and point_cloud_outlier_removal.2 are defined, to not do any filtering you must set the configuration of point_cloud_outlier_removal to None.

Examples

---
applications:
  point_cloud_outlier_removal.one: # the identifier can be set to anything
    method: small_components
    on_ground_margin: 10
    save_intermediate_data: true # the output folder will contain the identifier, to easily find it
  point_cloud_outlier_removal.two:
    method: statistical
    k: 10

{
    "applications": {
        "point_cloud_outlier_removal.one": {
            "method": "small_components",
            "on_ground_margin": 10,
            "save_intermediate_data": true
        },
        "point_cloud_outlier_removal.two": {
            "method": "statistical",
            "k": 10
        }
    }
}

---
applications:
  point_cloud_outlier_removal: null # disable any filtering

{
    "applications": {
        "point_cloud_outlier_removal": null
    }
}

---
applications:
  point_cloud_outlier_removal: # you can also just have a single filtering
    method: statistical
    k: 3

{
    "applications": {
        "point_cloud_outlier_removal": {
            "method": "statistical",
            "k": 3
        }
    }
}

Footnotes