Estimation of 3-D parametric models from shading image using genetic algorithms

In this paper, a method for estimating parameters of a 3-D shape from a 2-D shading image using a genetic algorithms (GAs) is proposed. The shape of the object is represented by a superquadrics model, and then the model parameters are coded for application to GAs. The coded string is evaluated according to the similarity of the shading image calculated from the 3-D model shape represented by the parameters to the given 2-D shading image. By applying the GAs to the optimization of the evaluation value, the string having the minimum difference can be found. The parameters are estimated from some shading images of various 3-D shapes by using the proposed method, and the results are presented.