Memetic electromagnetism algorithm for surface reconstruction with rational bivariate Bernstein basis functions
Surface reconstruction is a very important issue with outstanding applications in fields such as medical imaging (computer tomography, magnetic resonance) biomedical engineering (customized prosthesis and medical implants) computer aided design and manufacturing (reverse engineering for the automotive, aerospace and shipbuilding industries) rapid prototyping (scale models of physical parts from CAD data) computer animation and film industry (motion capture, character modeling) archaeology (digital representation and storage of archaeological sites and assets) virtual/augmented reality, and many others. In this paper we address the surface reconstruction problem by using rational Bezier surfaces. This problem is by far more complex than the case for curves we solved in a previous paper. In addition, we deal with data points subjected to measurement noise and irregular sampling, replicating the usual conditions of real world applications. Our method is based on a memetic approach combining a powerful metaheuristic method for global optimization (the electromagnetism algorithm) with a local search method. This method is applied to a benchmark of five illustrative examples exhibiting challenging features. Our experimental results show that the method performs very well, and it can recover the underlying shape of surfaces with very good accuracy.
Natural Computing