Recovering primitives in 3D CAD meshes

In an industrial context, recovering a continuous model is necessary to make modifications or to exchange data with a format including continuous representation of objects like STEP. But for many reasons, the initial continuous object can be lost after a display or an exchange with a discretized format. The mesh can also be deformed after a numerical computation. It is then important to have a method to create a new continuous model of the object from a mesh. In case of CAD object, the first step is to detect simple primitives like: plane, sphere, cone and cylinder from a 3D CAD mesh. This paper is focused on this step. This method of detection use curvature features to recover each primitive type. Segmentation is based on the curvature feature computed for each vertex. It permits to extract sub-meshes. Each one corresponds to a primitive. Parameters of these primitives are found with a fitting process according to the curvature features.

[1]  William Puech,et al.  Decomposition of a 3D Triangular Mesh into Quadrangulated Patches , 2018, GRAPP.

[2]  Ralph R. Martin,et al.  Algorithms for reverse engineering boundary representation models , 2001, Comput. Aided Des..

[3]  Claus Brenner,et al.  Curvature-based range image classification for object recognition , 2000, SPIE Optics East.

[4]  Marco Attene,et al.  Hierarchical mesh segmentation based on fitting primitives , 2006, The Visual Computer.

[5]  Francis Schmitt,et al.  Intrinsic Surface Properties from Surface Triangulation , 1992, ECCV.

[6]  Ralph R. Martin,et al.  Constrained fitting in reverse engineering , 2002, Comput. Aided Geom. Des..

[7]  Ilan Shimshoni,et al.  Robust Methods for Geometric Primitive Recovery and Estimation From Range Images , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[8]  S. S. Pande,et al.  Automatic recognition of features from freeform surface CAD models , 2008, Comput. Aided Des..

[9]  Ralph R. Martin,et al.  Reverse engineering of geometric models - an introduction , 1997, Comput. Aided Des..

[10]  Ehud Rivlin,et al.  A comparison of Gaussian and mean curvature estimation methods on triangular meshes of range image data , 2007, Comput. Vis. Image Underst..

[11]  Ralph R. Martin,et al.  Faithful Least-Squares Fitting of Spheres, Cylinders, Cones and Tori for Reliable Segmentation , 1998, ECCV.

[12]  Bf Buxton,et al.  Three-Dimensional Surface Curvature Estimation using Quadric Surface Patches , 2002 .

[13]  Reinhard Klein,et al.  Efficient RANSAC for Point‐Cloud Shape Detection , 2007, Comput. Graph. Forum.

[14]  Chenshi Dong,et al.  Curvatures estimation on triangular mesh , 2005 .