Softwares

The Mesh Processing Plateform (MEPP) of our research team (M2Disco)  is now publicly available. It is an open source plateform based on CGAL, Qt and libQGLViewer which supports Windows, Linux and Mac OS X. This plateform allow the processing of static and dynamic 3D meshes and contains differents processing tools from the team (curvature calculation, segmentation, MSDM perceptual metric, fast boolean operations, Joint compression/watermarking).

  
MSDM : A perceptual distance measure between 3D meshes

This measure is asymetric and provides a score which reflects the perceptual distance between two 3D objects; Its value tends toward 1 (theoretical limit) when the measured objects are visually very different and is equal to 0 for identical ones.

This metric is based on curvature tensors which are integrated over geodesic regions. The radius of these regions influences the results of the metric. Indeed, for a large radius, the metric is less sensitive to small details (it corresponds to the case where the observer is far from the objects for instance). We recommend 0.005 for a rather high sensitivity and 0.01 for a lower sensitivity.

Warning: this metric works only for two meshes sharing the same connectivity and same vertex order in the mesh files.

The MS-Windows executable is available here (last release 8/09/2009) and the source code is available here (8/09/2009).

The latest release (15/11/2010)  of MSDM  is available in the MEPP Plateform

References: 

Lavoué, G., Drelie Gelasca, E., Dupont, F., Baskurt, A., Ebrahimi, T., Perceptually driven 3D distance metrics with application to watermarking, SPIE Applications of Digital Image Processing XXIX, San Diego, August 2006.

3D mesh roughness calculation

This measure provides the roughness value for each vertex of a given 3D mesh, as a local measure of geometric noise. This estimator depends on a scale parameter epsilon which determines the size (i.e. the frequency) of the details that have to be considered as noise and that can lead to a masking effect.

The MS-Windows executable is available here (last release 4/09/2008).

Reference: Lavoué, G., A Local Roughness Measure for 3D Meshes and its Application to Visual Masking, ACM Transactions on Applied Perception, Vol. 5, No. 4, Article 21, 2009.

Mesh clustering based on Markov Random Field

This algorithm provides a clustering / labeling of a 3D mesh given any field of scalar values associated with its vertices. It is based on Markov Random Fields and allows to integrate both the attributes and the geometry in the clustering, while providing an optimal global solution.

It takes as inputs a mesh file (XXX.obj or XXX.off) and an attribute file (XXX_attribute.att) and the output is a Label file (XXX__labels.lb).

The MS-Windows executable is available here (last release 4/09/2008).

Reference: Lavoué, G. and Wolf, C., Markov Random Fields for Improving 3D Mesh Analysis and Segmentation, Eurographics 2008 Workshop on 3D Object Retrieval, pp. 25-32, Crete, Greece, April 2008.

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