Frank C Langbein
Ex Tenebris Scientia
Contents

F. C. Langbein, B. I. Mills, A. D. Marshall, R. R. Martin.

In: Proc. Int. Conf. Shape Modelling and Applications, IEEE Computer Society, pp. 10-19, 2001.
ISBN 0769508537.

[DOI: 10.1109/SMA.2001.923370] [Preprint] [CiteSeer]

Boundary representation models reconstructed from 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 regular geometric patterns approximately present in the model and imposes a maximal consistent subset of constraints deduced from these patterns on the model. This pa per presents analysis methods seeking geometric patterns defined by similarities. Their specific types are derived from a part survey estimating the frequencies of the patterns in simple mechanical components. The methods seek clusters of similar objects which describe properties of faces, loops, edges and vertices, try to find special values representing the clusters, and seek approximate symmetries of the model. Experiments show that the patterns detected appear to be suitable f o r the subsequent beautification steps. 

@INPROCEEDINGS{Langbein2001,
  author =       {Frank C. Langbein and Bruce I. Mills and A. Dave
                  Marshall and Ralph R. Martin},
  title =        {Recognizing Geometric Patterns for Beautification of
                  Reconstructed Solid Models},
  booktitle =    {Proc. Int. Conf. Shape Modeling and Applications},
  year =         2001,
  pages =        {10-19},
  address =      {Washington, DC, USA},
  publisher =    {IEEE Computer Society},
  isbn =         0769508537,
  doi =          {10.1109/SMA.2001.923370},
  url =          {http://www.langbein.org/research/solids/borg/langbein2001/},
  abstract =     {Boundary representation models reconstructed from
                  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 regular geometric
                  patterns approximately present in the model and
                  imposes a maximal consistent subset of constraints
                  deduced from these patterns on the model. This pa per
                  presents analysis methods seeking geometric patterns
                  defined by similarities. Their specific types are
                  derived from a part survey estimating the
                  frequencies of the patterns in simple mechanical
                  components. The methods seek clusters of similar
                  objects which describe properties of faces, loops,
                  edges and vertices, try to find special values
                  representing the clusters, and seek approximate
                  symmetries of the model. Experiments show that the
                  patterns detected appear to be suitable f o r the
                  subsequent beautification steps.},
}
Cite as Recognizing Geometric Patterns for Beautification of Reconstructed Solid Models, http://www.langbein.org/research/solids/borg/langbein2001 by Frank C Langbein [ 6/December/2008, 19:01].
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