Genetic Algorithms for Gielis Surface Recovery from 3D Data Sets
In this paper, we apply genetic algorithms to reconstruct Gielis surfaces from 3D data sets. The Levenberg-Marquardt method has been used as a standard for superquadrics recovery and has recently been extended to Gielis surfaces. Unfortunately, the non homogeneity of the Gielis surface parameters requires additional heuristic to determine discrete parameters such as the number of symmetries. Genetic algorithms overcome this issue and provide a more general framework for Gielis surface reconstruction.