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Simulated Annealing and Natural Neighbor for Rational Bézier Surface Reconstruction from Scattered Data Points

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Harmony Search Algorithm (ICHSA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 514))

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Abstract

Surface reconstruction is a very important problem in fields such as geometric modeling and processing, and CAD/CAM. Most of the methods proposed to solve this problem rely on parametric polynomial schemes. However, there are shapes that cannot be described by using a strictly polynomial approach. In this paper we introduce a new method to address the surface reconstruction problem from scattered data points through rational Bézier surfaces. Our approach is based on the combination of simulated annealing, the natural neighbor interpolation method, and least-squares minimization to perform data parameterization, data fitting, and weight computation. Some computer experiments carried out for both organized and unorganized data sets show the good performance of our approach.

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Acknowledgments

This work has been supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grants TEC2013-47141-C4-R (RACHEL) and #TIN2012-30768 (Computer Science National Program) and Toho University.

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Correspondence to Andrés Iglesias .

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Loucera, C., Iglesias, A., Gálvez, A. (2017). Simulated Annealing and Natural Neighbor for Rational Bézier Surface Reconstruction from Scattered Data Points. In: Del Ser, J. (eds) Harmony Search Algorithm. ICHSA 2017. Advances in Intelligent Systems and Computing, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-10-3728-3_35

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  • DOI: https://doi.org/10.1007/978-981-10-3728-3_35

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  • Print ISBN: 978-981-10-3727-6

  • Online ISBN: 978-981-10-3728-3

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