Frank C Langbein
Ex Tenebris Scientia
Contents

F. C. Langbein, A. D. Marshall, R. R. Martin.

In: H. Suzuki, R. R. Martin (eds), Proc. Geometric Modeling and Processing, IEEE Computer Society, pp. 159-168, 2002.
ISBN 0769516742.

[DOI: 10.1109/GMAP.2002.1027507] [Preprint] [CiteSeer]

Boundary representation models reconstructed from 3D range data suffer from various inaccuracies caused by noise in the data and the model building software. The quality of such models can be improved in a beautification step, which finds geometric regularities approximately present in the model and tries to impose a consistent subset of these regularities on the model. A framework for beautification and numerical methods to select and solve a consistent set of constraints deduced from a set of regularities are presented. For the initial selection of consistent regularities likely to be part of the model's ideal design priorities, and rules indicating simple inconsistencies between the regularities are employed. By adding regularities consecutively to an equation system and trying to solve it using quasi-Newton optimization methods, inconsistencies and redundancies are detected. The results of experiments are encouraging and show potential for an expansion of the methods based on degree of freedom analysis. 

@INPROCEEDINGS{Langbein2002,
  author =       {Frank C. Langbein and A. Dave Marshall and Ralph R.
                  Martin},
  title =        {Numerical Methods for Beautification of Reverse
                  Engineered Geometric Models},
  booktitle =    {Proc. Geometric Modeling and Processing---Theory and
                  Applications},
  year =         2002,
  editor =       {H. Suzuki and R. R. Martin},
  pages =        {159-168},
  address =      {Washington, DC, USA},
  publisher =    {IEEE Computer Society},
  isbn =         0769516742,
  doi =          {10.1109/GMAP.2002.1027507},
  url =          {http://www.langbein.org/research/solids/borg/langbein2002/},
  abstract =     {Boundary representation models reconstructed from 3D
                  range data suffer from various inaccuracies caused
                  by noise in the data and the model building
                  software. The quality of such models can be improved
                  in a beautification step, which finds geometric
                  regularities approximately present in the model and
                  tries to impose a consistent subset of these
                  regularities on the model. A framework for
                  beautification and numerical methods to select and
                  solve a consistent set of constraints deduced from a
                  set of regularities are presented. For the initial
                  selection of consistent regularities likely to be
                  part of the model's ideal design priorities, and
                  rules indicating simple inconsistencies between the
                  regularities are employed. By adding regularities
                  consecutively to an equation system and trying to
                  solve it using quasi-Newton optimization methods,
                  inconsistencies and redundancies are detected. The
                  results of experiments are encouraging and show
                  potential for an expansion of the methods based on
                  degree of freedom analysis.},
}
Cite as Numerical Methods for Beautification of Reverse Engineered Geometric Models, http://www.langbein.org/research/solids/borg/langbein2002 by Frank C Langbein [ 6/December/2008, 19:09].
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