Research
Publications
AMLS software can take a point cloud data possibly contaminated with noise and then smooth it out. A smooth surface can be reconstructed out of the output of AMLS. The software is based on a new definition of MLS surface that takes into account the features of the sampled surface. Also, the implicit function defining the AMLS surface is significantly different from the standard MLS surface definition. This new definition has several advantages over the standard one as explained in the paper given below.
The input to AMLS is a point cloud with assigned normals and features. The normals and features can be computed from a point cloud using the NormFet software given below. This means NormFet can create the input file for AMLS from an input point cloud.The output of AMLS can be fed to the Cocone software given below to reconstruct the surface.
Codes are available for Linux, and Windows.
Please send an email to tamaldey@cse.ohio-state.edu to get
the password to access the download area.
Paper for AMLS:
T. K. Dey and J. Sun. Adaptive
MLS Surfaces for Reconstruction with Guarantees. Proc. Eurographics
Symposium on Geometry Processing (2005), 43--52.
Paper for NormFet:
T. K. Dey and J. Sun. Normal
and Feature Estimations from Noisy Point Clouds. Technical Report
OSU-CISRC-7/50-TR50, July, 2005.
Additional recommendation:
T. K. Dey, S. Goswami and J.
Sun. Extremal
Surface Based Projections Converge and Reconstruct with Isotopy. Technical
Report OSU-CISRC-05-TR25, April, 2005.
Other Software : Cocone,
QualMesh,
Segmatch
Acknowledgements
The output of the AMLS software can be viewed with GEOMVIEW.
Disclaimer: We do not intend to be responsible for the maintenance of the software.
Copyright: Jyamiti group at the Ohio State University. No commercial use of the software is permitted without license.