Research on camera calibration optimization method based on chaotic sparrow search algorithm

In order to improve the low accuracy and poor reusability of camera parameter calibration, a camera parameter calibration optimization method based on Chaotic Sparrow Search Algorithm (SSA) is proposed. The method includes four steps: Firstly, the population is initialized by Tent chaotic sequence in order to improve the quality of the initial solution and the global search ability of the algorithm; Then, Gaussian mutation method is introduced to improve the local search ability and search accuracy; Thirdly, the Tent chaotic sequence is generated based on the search stagnation solution, and this chaotic sequence is used to carry out chaotic disturbance on some individuals trapped in local optimum, so that the algorithm jumps out of the limitation to continue searching, so as to obtain the initial estimation of the internal and external parameters of the camera, and then the operation interval of SSA is determined by the initial estimation; Finally, by establishing the average reprojection error equation and using SSA to calibrate and optimize the camera parameters in the determined interval, the smaller average reprojection error can be obtained. The experimental results show that the camera calibration parameter optimization method based on chaotic SSA has higher accuracy and better reusability, than Zhang Zhengyou calibration method and particle swarm calibration method.