Camera calibration with genetic algorithms

In this paper, we present a novel approach based on genetic algorithms for performing camera calibration. Contrary to the classical nonlinear photogra mmetric approach [1], the proposed technique can correctly find the near-op timal solution without the need of initial guesses (with only very loose pa rameter bounds) and with a minimum number of control points (7 points). Res ults from our extensive study using both synthetic and real image data as w ell as performance comparison with Tsai's procedure [2] demonstrate the exc ellent performance of the proposed technique in terms of convergence, accur acy, and robustness.