MeshLab is developed by the
ISTI -
CNR research center; initially MeshLab was created as a course assignment at the
University of Pisa in late 2005. It is a general-purpose system aimed at the processing of the typical not-so-small unstructured 3D models that arise in the
3D scanning pipeline. The automatic mesh cleaning filters includes removal of duplicated, unreferenced vertices, non-manifold edges, vertices, and null faces. Remeshing tools support high quality
simplification based on quadric error measure, various kinds of
subdivision surfaces, and two surface reconstruction algorithms from
point clouds based on the
ball-pivoting technique and on the Poisson surface reconstruction approach. For the removal of noise, usually present in acquired surfaces, MeshLab supports various kinds of
smoothing filters and tools for
curvature analysis and visualization. It includes a tool for the registration of multiple range maps based on the
iterative closest point algorithm. MeshLab also includes an interactive direct paint-on-mesh system that allows users to interactively change the color of a mesh, to define selections and to directly smooth out noise and small features. MeshLab is available for most platforms, including
Linux,
Mac OS X,
Windows and, with reduced functionality, on
Android and
iOS and even as a pure
client-side JavaScript application called MeshLabJS. The system supports input/output in the following formats:
PLY,
STL,
OFF,
OBJ,
3DS,
VRML 2.0,
X3D and
COLLADA. MeshLab can also import point clouds reconstructed using
Photosynth. MeshLab is used in various academic and research contexts, like microbiology,
cultural heritage, surface reconstruction, paleontology, for
rapid prototyping in
orthopedic surgery, in
orthodontics, and
desktop manufacturing. == Additional images ==