Camera calibration is very important in machine vision technology.In view of the cumbersome operation of the traditional 3D object calibration method and the influence of the initial weight and threshold value on the BP neural network calibration, this paper proposes a mind evolution neural network calibration method based on the optical axis convergence model.The BP neural network algorithm can approach nonlinear function, and mind evolution algorithm has strong global optimization ability.Therefore, the problems of BP neural network such as easily falling into local minimum and randomization of initial weight and threshold can be effectively solved.Experiments show that, compared with the classical Zhang Zhengyou calibration method and BP neural network method,the mind evolution neural network calibration method can achieve better accuracy of binocular calibration.