Zhenjue tutorial : Différence entre versions

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==Description==
 
==Description==
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The folder contain 30 JPG files. In this dataset there isn't any data about the camera which was used. The shooting set contains 30 images, all taken with the Canon 70D camera with an 18mm lens. The camera saves metadata for all the pictures (exif data). If you are looking in the property data of each pictures, the 18mm lens is mentionned and the various chosen settings while the production of this dataset was realized (opening, break, ...). <br>
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This dataset contain images with different focal legnth (24 and 100 mm).
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There are 5 parts in this dataset :
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*4 parts includes 4 differents points of view of the fountain. Each part was created with a cross points of view. This means there is one master image at the center and 4 images around it (top, bottom, left and right from the master image).
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*1 part contain the others images (IMG.*JPG). These images are images link, this means that they will allow to link the 4 other parts together. There won't be used to generate the dense clouds points. <br>
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We will work this dataset with the image geometry pattern, that means that we will choose one master image, and from this image, it will compute a depth map. This master image can't cover the whole object at 360degree. To modelize this 3D object, we need to calculate a few more depth maps with the image geometry pattern, in order to get the whole 3D fountain. In this exercise, we will calculate 4 depth maps : one for each part.
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==Tutorial==
 
==Tutorial==

Version du 9 mars 2016 à 22:22

Picto-liste.png Tutorial index

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).

Tutorial

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=Toutes

Dense correlation in image geometry

Edit selection

mm3d SaisieMasq DSC_3128.JPG
mm3d SaisieMasq DSC_3135.JPG

Dense correlation

mm3d Malt GeomImage "DSC_31((2[5-9])|(3[0-1])).JPG" Toutes Master=DSC_3128.JPG ZoomF=4
mm3d Malt GeomImage "DSC_313[2-9].JPG" Toutes 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
Récupérée de « http://micmac.ensg.eu/index.php?title=Zhenjue_tutorial&oldid=1588 »