Zhenjue tutorial
De MicMac
Révision de 9 mars 2016 à 22:35 par Dias (discussion | contributions) (→Dense correlation in image geometry)
Sommaire
Download
- There is a direct download link to download this dataset at :
Once you have download it, you have to UnZip the ".zip" archive.
Description
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).
Tutorial
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
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