Zhenjue tutorial

De MicMac
Révision de 9 mars 2016 à 23:36 par Dias (discussion | contributions) (Create & edit a mask)

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  • There is a direct download link to download this dataset at :

Once you have download it, you have to UnZip the ".zip" archive.


This dataset contain images with different focal legnth (24 and 100 mm). The purpose of this tutorial is to reconstruct each statue idependently (warrior and musician). We will show two methods to reconstruct object in 3D by image geometry (Malt and PIMs).


1.Relative orientation

Compute tie points

mm3d Tapioca All  ".*JPG" 1500

Compute relative orientation for images with specified focal length

mm3d Tapas RadialStd ".*JPG" Focs=[20,30] Out=F24

Check residual and number of points used per images.

Compute relative orientation for all images

mm3d Tapas RadialStd ".*JPG" InOri=F24 Out=All

Generate a sparse cloud for relative orientation

We will now generate a sparse cloud to visualize the relative orientation.

mm3d AperiCloud ".*JPG" All

Dense correlation in image geometry (old method)

For this part and the rest of this tutorial, we will focus only on the warrior.

Create & edit a mask

Define a mask for dense correlation can be done with the command SaisieMasqQT

mm3d SaisieMasqQT "DSC_3128.JPG"

Dense correlation

mm3d Malt GeomImage "DSC_313[2-9].JPG" All Master=DSC_3135.JPG ZoomF=4 AffineLast=0

Compute a depth map

cd MM-Malt-Img-DSC_3128
mm3d GrShade Z_Num6_DeZoom4_STD-MALT.tif ModeOmbre=IgnE Mask=AutoMask_STD-MALT_Num_5.tif FZ=2 Out=../Shade3128.tif
mm3d Nuage2Ply NuageImProf_STD-MALT_Etape_6.xml Attr=../DSC_3128.JPG RatioAttrCarte=4 Out=../3128.ply
cd MM-Malt-Img-DSC_3135
mm3d Nuage2Ply NuageImProf_STD-MALT_Etape_6.xml Attr=../DSC_3135.JPG RatioAttrCarte=4 Out=../3135.ply
mm3d GrShade Z_Num6_DeZoom4_STD-MALT.tif ModeOmbre=IgnE Mask=AutoMask_STD-MALT_Num_5.tif FZ=2 Out=../Shade3135.tif