摄像机标定是计算机视觉领域的一个研究热点，为了解决单目摄像机标定中的精度不高、模型复杂、鲁棒性差等问题，依

据神经网络、遗传算法及摄像机标定的特点，提出了基于遗传算法和BP神经网络相结合的单目摄像机标定方法。该方法充分利用

遗传算法的全局优化和神经网络的局部收敛的特点，一方面避免了建立复杂的摄像机成像模型，另一方面增强了摄像机标定的精

度和鲁棒性。-The camera calibration isoneofmostimportantresearch ifeldsin computervision．In orderto solve the questions of

imprecision，strutting complex model，non-orhustness in the camera calibration．In the paper，a algoirthm of camera calibration

based on BP neuralnetwork and genetic algoirthm isproposed according as characteirstic ofneuralnetwork，genetic algoirthm

and camera claibration．n1e algorithm makesfulluse ofglobalnumericaloptimization characteirsticin genetic algorithm and easily

converging to local minimum in neural newt ork．On the one hand，itdoes not need to build the complex camera imaging model，

on hteotherhand．itisimprovingthe precision and robustnessin the cma era calibration