3D drawing - week 2

Code on Github.

pickle scanner

yin+rose


The first assignment for the class 3d sensing & visualization taught by Kyle McDonald is to make a 3d scanner.

Rose and I made a pickle scanner.

how it works:
a pickle is submerged fully in water in a box

 the water is dyed with black ink

 a cover made of cardboard has a 12 x 9 grid drawn on it. A hole is poked through each square on the grid

 long sticks are inserted vertically down each hole on the grid, wherever it hits the pickle underneath, it doesn’t reach the bottom and hence sticks out more than the other sticks, thus creating a shape of the pickle above the grid cover

after a while, sticks are taken out, and readings are made on how much of the stick is colored with ink

these are the depth readings of the pickle

 combined with the grid coordinates (x and y) we have 3 D point cloud data

 raw measurements

visualizations in processing


 point cloud


 lines


it’s a pickle 

 other interesting shapes formed by imperfect data:

Reconstructing a Mesh from a Point Cloud

I posted a video describing one way to reconstruct a mesh from a point cloud in Meshlab, based on some info at the Meshlab blog.

Poisson Reconstruction in Meshlab from Kyle McDonald on Vimeo.

And I got a bunch of great tips from Sophie Barret-Kahn: here's an academic paper reporting on the different software that's available.

Rhino has a lot of tools for meshing, re-meshing, and surfacing (making parametrized functions that describe the mesh). Here's one for working with a point cloud:

There's more info on the Rhino tools here.

If you're more of a nerd, Matlab has some good low-level tools for handling this kind of data.

Finally, Blender has its own tools for dealing with mesh reconstruction. Taylor Goodman, who developed a structured light scanner for Makerbot, has a tutorial describing how to reconstruct a mesh for 3d printing from a point cloud:

I think there is a script for this on blenderartists but the site is broken at the moment.