Abstract
In Computer Aided Geometric Design (CAGD) the automated fitting of surfaces to massive series of data points presents several difficulties: (i) even the formal definition of the problem is ambiguous because the mathematical characteristics (continuity, for example) of the surface fit are dependent on non-geometric considerations, (ii) the data has an stochastic sampling component that cannot be taken as literal, and, (iii) digitization characteristics, such as sampling interval and directions are not constant, etc. In response, this investigation presents a set of computational tools to reduce, organize and re-sample the data set to fit the surface. The routines have been implemented to be portable across modeling or CAD servers. A case study is presented from the footwear industry, successfully allowing the preparation of a foreign, neutral laser digitization of a last for fitting a B-spline surface to it. Such a result was in the past attainable only by using proprietary software, produced by the same maker of the digitizing hardware.
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© 1999 Springer Science+Business Media Dordrecht
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Ruiz, O.E., Posada, J.L. (1999). Computational Geometry in the Preprocessing of Point Clouds for Surface Modeling. In: Batoz, JL., Chedmail, P., Cognet, G., Fortin, C. (eds) Integrated Design and Manufacturing in Mechanical Engineering ’98. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9198-0_23
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DOI: https://doi.org/10.1007/978-94-015-9198-0_23
Publisher Name: Springer, Dordrecht
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