Recommended file: Lucy_3M_O10_20%.stl
Update2: A print of the head at 50% scale, printed at a layer height of 0.3, looks very nice. At this scale, the statue would be 70 cm high. I'm now very motivated to build a Rostock derivative, although that would normally only allow 40 cm height.
Update: The mesh was sampled with 3M points, then an out of core Poisson reconstruction applied, followed by quadric edge collapse decimation (to 20%, hence the filename). The result is a 22 MB Mesh much better than the Lucy_simplified, at no extra size. I really need to document this all logically, this might not be the best place for it.
Taken from the Stanford 3D scanning site (graphics.stanford.edu/data/3Dscanrep/). The Stanford CGL asks that this model not be transfomed, morphed etc.
The original file was not manifold, making a straightforward simplification in MeshLab (see www.thingiverse.com/thing:40632) difficult. As a workaround, the statue was subsampled to 500K points in CloudCompare (www.danielgm.net/cc/). A reconstrucion of the resulting point-cloud should be possible with the poisson-reconstruction function in CloudCompare. As I am more familiar in Meshlab, I used that instead.
The workflow for a point-cloud to volume conversion is as follows:
Filters > Point Set > Estimate radius from density
Filters > Point Set > Compute normals for point sets
Filters > Remeshing, etc > Surface Reconstruction: Poisson (I used Octree Depth: 9)
Netfabb repair, due to some small errors
Update: I've uploaded the script for a surface reconstruction in MeshLab (.mlx):
Filters > Show current filter script
Open script > "Surface reconstruction.mlx"
The parameters for all stages in the script can be changed beforehand, then everything can be executed at once. MeshLab also installs a server, so the script can be executed from the command line. This however is more useful when working on a lot of models at once.
Slicing at 25% scale (200 mm wide at 45Ã‚Â°, 400 mm high) for a maximum Rostock build goes to 6 GB in RAM on my machine, so it is probably impractical to use a model with less simplification. The original model, converted to .stl, can surpass 14 GB in RAM when manipulated in Meshlab, so the point-cloud has also been included (.asc), for those wanting to try out this method. The original Model can be downloaded from the Stanford CGL site.