A genetic algorithm for recovering camera parameters and motion from silhouettes

We present a novel approach for recovering the camera parameters and motion from the concept of coherence of a set of silhouettes of an object taken under circular motion. These parameters can be obtained by maximizing the total coherence between all silhouettes. For this purpose, we propose in this paper to use genetic algorithm instead the conventional optimization procedures. Genetic algorithm can correctly find the optimal solution without the need of initial values of parameters. The performance of the proposed method is shown in term of convergence and accuracy to recover camera parameters. The recovered parameters may be used for 3D image-based modeling to obtain high quality 3D reconstructions.