Monocular Camera Calibration based on Genetic Simulated Annealing Algorithms

Abstract

This study presents a nonlinear camera calibration approach based on combining genetic and simulated annealing algorithms. This is a global optimization technique, which combines simulated annealing with genetic algorithms to find the optimal camera's intrinsic and extrinsic parameters. Since this matter is considered an optimization problem by several studies, a novel hybrid approach was developed and studied based on two powerful nature-inspired techniques to find the intrinsic and extrinsic parameters of the camera. Numerous experiments were conducted to evaluate the efficiency of the proposed approach. The results demonstrate that the proposed hybrid approach is robust, reliable, and accurate.