Robust camera parameter estimation using genetic algorithm

We propose a genetic algorithm based approach to determine the external parameters of the camera from the knowledge of a given set of points in object space. We study the effect of noise and presence of outliers, resulting from incorrect correspondences between the object space points and the image space points, on the estimation of three translation parameters and two rotational parameters of a camera. The average of the magnitudes of the translation errors varies from 2.25 cm. to 5 mm. and the average of the magnitudes of the rotational errors varies from 0.9 degree to 0.25 degree at 20 dB SNR. The error in parameter estimation is insignificant up to 3 pairs of mismatched points out of 20 points in object space and skyrockets when 4 or more pairs of points are mismatched. These results have clearly established the robustness of genetic algorithm in external camera parameter estimation.