Camera calibration with genetic algorithms

We present a novel approach based on genetic algorithms for performing camera calibration. Contrary to the classical nonlinear photogrammetric approach, the proposed technique can correctly find the near-optimal solution without the need of initial guesses (with only very loose parameter bounds) and with a minimum number of control points (7 points). Results from our extensive study using both synthetic and real image data as well as performance comparison with Tsai´s procedure demonstrate the excellent performance of the proposed technique in terms of convergence, accuracy, and robustness.