runICP Run ICP algorithm.
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DESCRIPTION/NOTES
With this method the global ICP process is started. For a short description of
the ICP algorithm, run 'help globalICP.globalICP'.
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INPUT
1 GENERAL ICP
a ['MaxNoIt', MaxNoit]
Maximum number of ICP iterations.
b ['IdxFixedPointClouds', IdxFixedPointClouds]
Index i of fixed point cloud. Index i refers to obj.PC{i}. To fix more
than one point cloud, multiple values can be defined as row vector.
c ['NoOfTransfParam', NoOfTransfParam]
Number of transformation parameters that are used in the ICP algorithm for
the transformation of the loose point clouds. Possible choices are 1, 3,
6, 7 or 12:
* 1 = only z translation parameter.
* 3 = only 3 translation parameters (in x, y, and z).
* 6 = rigid body transformation, i.e. 3 translation parameters plus
3 rotational parameters.
* 7 = similarity transformation, i.e. rigid body transformation plus an
additional scale parameter.
* 12 = affine transformation (9 parameters) and 3 translation
parameters.
2 DETERMINE POINT CLOUD OVERLAP
a ['HullVoxelSize', HullVoxelSize]
Voxel size of voxel hulls. The voxel hulls are used to determine the
overlap between the point clouds. This parameter defines the voxel size
(equal to edge length) of a single voxel.
Side note: What is the voxel hull of a point cloud?
The voxel hull is a low resolution representation of the volume occupied
by a point cloud. For the computation of the voxel hull the object space
is subdivided into a voxel structure. The voxel hull of the point cloud
consists of all voxels which contain at least one point of the point
cloud.
3 SELECTION OF CORRESPONDENCES
a ['UniformSamplingDistance', UniformSamplingDistance]
Mean distance between corresponding points. The selection of
correspondences is based on a uniform sampling strategy. For this a voxel
structure is derived from the point clouds and those points which are
closest to each voxel center are selected. This parameter defines the edge
length of the voxels. This strategy leads to a homogeneus distribution of
the selected points in object space.
4 PLANE FITTING
a ['PlaneSearchRadius', PlaneSearchRadius]
Search radius for plane fitting. All points within the search radius are
considered for the plane fitting. A good choice of the search radius is
based on the point cloud density and the geometry of the scanned object.
Note: to ensure a certain redundancy, planes are only considered if the
search area contains at least 8 points.
5 WEIGHTING
a ['WeightByRoughness', WeightByRoughness]
Logical value defining if correspondences are weighted on basis of the
roughness of corresponding points.
b ['WeightByDeltaAngle', WeightByDeltaAngle]
Logical value defining if correspondences are weighted on basis of the
angle between the normals of corresponding points.
6 REJECTION OF CORRESPONDENCES
a ['MaxDeltaAngle', MaxDeltaAngle]
Maximum allowed angle (in degree) between normals of corresponding points.
b ['MaxDistance', MaxDistance]
Maximum allowed point to point distance between corresponding points.
c ['MaxSigmaMad', MaxSigmaMad]
This option is used to remove correspondence outliers. All correspondences
with a point to plane distance (dp) outside the range
[-MaxSigmaMad*SigmaMad(dp) +MaxSigmaMad*SigmaMad(dp)] are rejected.
Note: SigmaMad is a robust estimator for the standard deviation of a data
set under the assumption that the set has a Gaussian distribution:
SigmaMad = 1.4812 * mad; where mad is the median of the absolute
differences (with respect to the median) of the data set.
d ['MaxRoughness', MaxRoughness]
Maximum allowed roughness of extracted planes. As roughness measure the
standard deviation of plane fitting is used.
7 REPORT
a ['LogLevel', LogLevel]
Possible choices:
* 'debug' -> all informations are displayed in workspace.
* 'basic' -> only basic informations are displayed in workspace.
* 'off' -> no informations are displayed in workspace.
b ['Plot', Plot]
If true, the point clouds are visualized after each ICP iteration.
8 ADVANCED PARAMETERS
a ['SubsetRadius', subsetRadius]
Radius for the selection of point cloud subsets. Background: for large
point clouds, usually it is not possible to load all point clouds in
memory simultaneously. Thus, only a small subset of points has to be
selected for each point cloud. For this points are selected around the
established correspondences within a specific radius, which is defined by
this parameter.
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CODEBLOCK FOR INPUT PARAMETERS
ICPOptions.MaxNoIt = ;
ICPOptions.IdxFixedPointClouds = ;
ICPOptions.NoOfTransfParam = ;
ICPOptions.HullVoxelSize = ;
ICPOptions.UniformSamplingDistance = ;
ICPOptions.PlaneSearchRadius = ;
ICPOptions.WeightByRoughness = ;
ICPOptions.WeightByDeltaAngle = ;
ICPOptions.MaxDeltaAngle = ;
ICPOptions.MaxDistance = ;
ICPOptions.MaxSigmaMad = ;
ICPOptions.MaxRoughness = ;
ICPOptions.LogLevel = ;
ICPOptions.Plot = ;
ICPOptions.SubsetRadius = ;
Undocumented parameters
ICPOptions.PairList = ;
ICPOptions.RandomSubsampling = ;
ICPOptions.NormalSubsampling = ;
ICPOptions.MaxLeverageSubsampling = ;
ICPOptions.SubsamplingPercentPoi = ;
ICPOptions.AdjOptions = ;
ICPOptions.MinNoIntersectingVoxel = ;
ICPOptions.TrafoOriginalPointClouds = ;
ICPOptions.StopConditionNormdx = ;
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REFERENCES
[1] Glira, P., Pfeifer, N., Ressl, C., Briese, C. (2015): A correspondence
framework for ALS strip adjustments based on variants of the ICP
algorithm. In: Journal for Photogrammetry, Remote Sensing and
Geoinformation Science (PFG) 2015(04), pp. 275-289.
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philipp.glira@gmail.com
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