Genetic Algorithms for Free-Form Surface Matching
The free-form surface matching problem is important in several practical
applications, such as reverse engineering. An accurate, robust and fast
solution is, therefore, of great significance.
Recently genetic algorithms have attracted
great interest for their ability to robustly solve hard optimization problems. In
this work we investigate the performance of such an approach fornadading
theCVAP/ initial guess of the transformation, a translation and a rotation,
between the object and the model surface. This would be followed by a local
gradient descent method such as ICP to refine the estimate.
The algorithm is simple and promising results are demonstrated on
accurate real data.