M3C2 (plugin) - Revision history

Daniel at 18:55, 4 July 2019

2019-07-04T18:55:13Z

← Older revision		Revision as of 20:55, 4 July 2019
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	Since version 2.10, one can call the M3C2 plugin via the command line.		Since version 2.10, one can call the M3C2 plugin via the command line.

	Basically, ~~just~~ load 2 clouds, ~~then~~ call the "-M3C2" command with a M3C2 parameters file as argument. This file can be saved via the dialog of the standard version. It should then be easy to update to your needs.		Basically, you need to load at least 2 clouds (if a 3rd cloud is present, it will be used as core points). Then call the "-M3C2" command with a M3C2 parameters file as argument. This file can be saved via the dialog of the standard version. It should then be easy to update to your needs.

			'''CloudCompare -O cloud1 -O cloud2 (-O core_points) -M3C2 parameters_file'''

Daniel at 18:50, 4 July 2019

2019-07-04T18:50:04Z

← Older revision		Revision as of 20:50, 4 July 2019
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	'''For a clearer display, you should create your own absolute color scale, with you own labels, etc. Use the [[Scalar_fields%5CColor_Scales_Manager \| Color Scales manager]] to do it.'''		'''For a clearer display, you should create your own absolute color scale, with you own labels, etc. Use the [[Scalar_fields%5CColor_Scales_Manager \| Color Scales manager]] to do it.'''

			= Command line =

			Since version 2.10, one can call the M3C2 plugin via the command line.

			Basically, just load 2 clouds, then call the "-M3C2" command with a M3C2 parameters file as argument. This file can be saved via the dialog of the standard version. It should then be easy to update to your needs.

Daniel: /* Introduction */

2018-02-23T08:53:30Z

Introduction

← Older revision		Revision as of 10:53, 23 February 2018
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	[[File:M3C2_illustration.jpg\|center\|frame]]		[[File:M3C2_illustration.jpg\|center\|frame]]

	While you can use the 'Guess params' button, it is highly advised to read (even quickly) the original [~~http~~://~~www~~.~~geosciences.univ-rennes1.fr/IMG~~/pdf/~~Accurate_3D_point_cloud_comparison_Lague_et_al-_revised_with_figures_feb2013~~.~~pdf~~ article] by D. Lague, N. Brodu and J. Leroux (Geosciences Rennes).		While you can use the 'Guess params' button, it is highly advised to read (even quickly) the original [https://arxiv.org/pdf/1302.1183 article] by D. Lague, N. Brodu and J. Leroux (Geosciences Rennes).

	'''Precision Maps'''		'''Precision Maps'''

Daniel: /* Computing distance */

2017-10-22T09:03:49Z

Computing distance

← Older revision		Revision as of 11:03, 22 October 2017
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	Note also that points without any corresponding points in the other cloud stay in 'gray' (they are associated to ''NaN'' - not a number - distances). This means that no points in the other cloud could be found inside the search cylinder. Therefore, gray points means that either some parts of the clouds have no equivalent in the other cloud (due to hidden parts or other holes in the datasets) or simply that the cylinder maximum length is not long enough!		Note also that points without any corresponding points in the other cloud stay in 'gray' (they are associated to ''NaN'' - not a number - distances). This means that no points in the other cloud could be found inside the search cylinder. Therefore, gray points means that either some parts of the clouds have no equivalent in the other cloud (due to hidden parts or other holes in the datasets) or simply that the cylinder maximum length is not long enough!

			'''For a clearer display, you should create your own absolute color scale, with you own labels, etc. Use the [[Scalar_fields%5CColor_Scales_Manager \| Color Scales manager]] to do it.'''

Daniel: /* Computing M3C2 distances */

2017-10-22T09:01:33Z

Computing M3C2 distances

← Older revision		Revision as of 11:01, 22 October 2017
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	Select the two clouds you want to compare then call the 'Plugins > M3C2 Distance' method.		Select the two clouds you want to compare then call the 'Plugins > M3C2 Distance' method.

	[[File:M3c2_dialog.jpg\|center~~\|frame~~]]		[[File:M3c2_dialog.jpg\|center]]

	== Main parameters ==		== Main parameters ==

Daniel: /* Precision maps */

2017-10-22T08:59:41Z

Precision maps

← Older revision		Revision as of 10:59, 22 October 2017
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	The Precision maps tab enables the calculation of detectable change to be carried out using measurement precision values stored in scalar fields of point clouds, rather than being estimated from roughness calculations.		The Precision maps tab enables the calculation of detectable change to be carried out using measurement precision values stored in scalar fields of point clouds, rather than being estimated from roughness calculations.

	This ‘PM’ variant of M3C2 is described in James et al. (2017) and allows photogrammetric precision estimates to be used directly within the M3C2 workflow.		This ‘PM’ variant of M3C2 is described in [http://dx.doi.org/10.1002/esp.4125 James et al. (2017)] and allows photogrammetric precision estimates to be used directly within the M3C2 workflow.

	If scalar fields are available, then the check box can be used to enable the ‘precision maps’ variant of M3C2. In this case, uncertainty estimates will no longer be made from roughness estimates at the projection scale in the Main Parameters tab, but will be based on 3-D point precision estimates stored in scalar fields. '''Ensure that the appropriate scalar fields are selected for both point clouds to describe measurement precision in X, Y and Z''' (sigmaX, sigmaY and sigmaZ).		If scalar fields are available, then the check box can be used to enable the ‘precision maps’ variant of M3C2. In this case, uncertainty estimates will no longer be made from roughness estimates at the projection scale in the Main Parameters tab, but will be based on 3-D point precision estimates stored in scalar fields. '''Ensure that the appropriate scalar fields are selected for both point clouds to describe measurement precision in X, Y and Z''' (sigmaX, sigmaY and sigmaZ).

Daniel: /* Introduction */

2017-10-22T08:59:26Z

Introduction

← Older revision		Revision as of 10:59, 22 October 2017
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	'''Precision Maps'''		'''Precision Maps'''

	Since version 2.9, the M3C2 plugin also includes the ‘precision maps’ (M3C2-PM) variant of James et al. (2017), for when precision estimates are already available for each point, and don’t need to be calculated from roughness estimates. M3C2-PM is particularly suited to point clouds generated by photogrammetric processing; see the dedicated section below and [http://dx.doi.org/10.1002/esp.4125 James et al. (2017)] for more details.		Since version 2.9, the M3C2 plugin also includes the ‘precision maps’ (M3C2-PM) variant of [http://dx.doi.org/10.1002/esp.4125 James et al. (2017)], for when precision estimates are already available for each point, and don’t need to be calculated from roughness estimates. M3C2-PM is particularly suited to point clouds generated by photogrammetric processing; see the dedicated section below and [http://dx.doi.org/10.1002/esp.4125 James et al. (2017)] for more details.

	[[File:M3c2_precision_maps.jpg\|center]]		[[File:M3c2_precision_maps.jpg\|center]]

Daniel: /* Precision maps */

2017-10-22T08:58:52Z

Precision maps

← Older revision		Revision as of 10:58, 22 October 2017
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	== Precision maps ==		== Precision maps ==

	[~~Image \|~~ M3c2_precision_maps_tab.JPG]		[[File:M3c2_precision_maps_tab.JPG\|center]]

	The Precision maps tab enables the calculation of detectable change to be carried out using measurement precision values stored in scalar fields of point clouds, rather than being estimated from roughness calculations.		The Precision maps tab enables the calculation of detectable change to be carried out using measurement precision values stored in scalar fields of point clouds, rather than being estimated from roughness calculations.

Daniel: /* Precision maps */

2017-10-22T08:58:02Z

Precision maps

← Older revision		Revision as of 10:58, 22 October 2017
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	== Precision maps ==		== Precision maps ==

	The Precision maps tab enables the calculation of detectable change to be carried out using measurement precision values stored in scalar fields of point clouds, rather than being estimated from roughness calculations. This ‘PM’ variant of M3C2 is described in James et al. (2017) and allows photogrammetric precision estimates to be used directly within the M3C2 workflow.		[Image \| M3c2_precision_maps_tab.JPG]
	If scalar fields are available, then the check box can be used to enable the ‘precision maps’ variant of M3C2. In this case, uncertainty estimates will no longer be made from roughness estimates at the projection scale in the Main Parameters tab, but will be based on 3-D point precision estimates stored in scalar fields. Ensure that the appropriate scalar fields are selected for both point clouds to describe measurement precision in X, Y and Z (sigmaX, sigmaY and sigmaZ). The scale can be changed if the precision values are in different units to the point coordinates. For example, if point coordinates and precision values are in metres, then the scale value is 1.000. However, if coordinates are in metres, but the scalar fields of precision are provided in millimetres, then the scale value should be set to 0.001.
			The Precision maps tab enables the calculation of detectable change to be carried out using measurement precision values stored in scalar fields of point clouds, rather than being estimated from roughness calculations.

			This ‘PM’ variant of M3C2 is described in James et al. (2017) and allows photogrammetric precision estimates to be used directly within the M3C2 workflow.

			If scalar fields are available, then the check box can be used to enable the ‘precision maps’ variant of M3C2. In this case, uncertainty estimates will no longer be made from roughness estimates at the projection scale in the Main Parameters tab, but will be based on 3-D point precision estimates stored in scalar fields. '''Ensure that the appropriate scalar fields are selected for both point clouds to describe measurement precision in X, Y and Z''' (sigmaX, sigmaY and sigmaZ).

			The scale can be changed if the precision values are in different units to the point coordinates. For example, if point coordinates and precision values are in metres, then the scale value is 1.000. However, if coordinates are in metres, but the scalar fields of precision are provided in millimetres, then the scale value should be set to 0.001.

	== Advanced ==		== Advanced ==

Daniel: /* Introduction */

2017-10-22T08:51:04Z

Introduction

← Older revision		Revision as of 10:51, 22 October 2017
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	Since version 2.9, the M3C2 plugin also includes the ‘precision maps’ (M3C2-PM) variant of James et al. (2017), for when precision estimates are already available for each point, and don’t need to be calculated from roughness estimates. M3C2-PM is particularly suited to point clouds generated by photogrammetric processing; see the dedicated section below and [http://dx.doi.org/10.1002/esp.4125 James et al. (2017)] for more details.		Since version 2.9, the M3C2 plugin also includes the ‘precision maps’ (M3C2-PM) variant of James et al. (2017), for when precision estimates are already available for each point, and don’t need to be calculated from roughness estimates. M3C2-PM is particularly suited to point clouds generated by photogrammetric processing; see the dedicated section below and [http://dx.doi.org/10.1002/esp.4125 James et al. (2017)] for more details.

	[[File:M3c2_precision_maps.jpg\|center~~\|frame~~]]		[[File:M3c2_precision_maps.jpg\|center]]

	= Computing M3C2 distances =		= Computing M3C2 distances =