AperiCloud

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Description

AperiCloud is used for generating a visualization of and sparse 3D model and cameras position, computed by Tapas for example.

Syntax

The global syntax for AperiCloud is :

mm3d AperiCloud FullName Orientation NamedArgs

Results

AperiCloud, generate a sparse 3D cloud (".ply") with the position and orientation of each camera. If you don't use "Out" option, the file will be stored in your working directory at the name : AperiCloud-Ori_Name.ply. You can use MeshLab to visualize the file.
01 Gravillonn AO.jpg Pierrerue2.png Exercice Fontaine1.png

Workflow

AperiCloud is a tool dedicated to visualization of orientations. So you can use it every times you process a orientation. When you have processed the final orientation, you can define a 3D mask with the ".ply" file generated by AperiCloud (SaisieMasqQT).
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Help

You can access to the help by typing :

mm3d AperiCloud -help

Mandatory unnamed args :

  • string :: {Full name (Dir+Pattern)}
  • string :: {Orientation directory}

Named args :

  • [Name=ExpTxt] INT :: {Point in txt format ? (Def=false)}
  • [Name=Out] string :: {Result (Def=AperiCloud.ply)}
  • [Name=Bin] INT :: {Ply in binary mode (Def=true)}
  • [Name=RGB] INT :: {Use RGB image to texturate points (Def=true)}
  • [Name=SeuilEc] REAL :: {Max residual (Def=10)}
  • [Name=LimBsH] REAL :: {Limit ratio base to height (Def=1e-2)}
  • [Name=WithPoints] bool :: {Do we add point cloud? (Def=true) }
  • [Name=CalPerIm] bool :: {If a calibration per image was used (Def=false)}
  • [Name=Focs] Pt2dr :: {Interval of Focal}
  • [Name=WithCam] bool :: {With Camera (Def=true)}
  • [Name=ColCadre] Pt3di :: {Col of camera rect Def= 255 0 0 (Red)}
  • [Name=ColRay] Pt3di :: {Col of camera rect Def= 0 255 0 (Green)}
  • [Name=SH] string :: {Set of Hom, Def="", give MasqFiltered for result of HomolFilterMasq}

Example

In example, you can launch this command in the Mur Saint Martin dataset :

mm3d AperiCloud «.*JPG » Out=MEP 

Known limitations

AperiCloud doesn't support 64 bits ply

Use of AperiCloud with coordinates with many digits generates models which seeems sliced, or very sparse, because this tool doesn't support 64 bits ply models.

Due to this limitations, it is recommended to use local or truncated coordinate. Or not to use AperiCloud after georeferencement in a projected coordinates system. Look to this thread for an example and further information.

For precision and accuracy reasons, it is anyways always recommended to work in a local system at least until just before the correlation step (after Campari), and use ChgSysCo to then get to the projected coordinate system.