Camera Calibration Based on Elitist Genetic Algorithm

Abstract

Camera calibration presents an essential computer vision task for many applications, including augmented reality, 3D reconstruction, and object tracking. In this paper, we present an elitist genetic algorithm for camera calibration to determine the intrinsic and extrinsic camera parameters, then a comparison of the proposed algorithm and standard genetic algorithm. The primary goal is the use of fitness function minimization to identify the best solution for the camera parameters. Proposed method is robust and gives good results as demonstrated by our experiments.