摘要
针对BP神经网络在双目相机标定时受到初始权值和阈值的影响,提出了一种基于改进遗传算法优化BP神经网络对双目相机进行标定的方法,通过对遗传算法的交叉和变异概率进行改进,采用世界坐标值直接对比度使得数据更直观,实验证明可以获得更高的精度。
In binocular camera calibration,BP neural network is affected by initial weights and thresholds.A method based on BP neural network optimized by the improved genetic algorithm is proposed to solve the problem.The crossover and mutation probabilities of the genetic algorithm are improved.The direct contrast of world coordinates is adopted to make the data more intuitive.The experiment shows that higher accuracy can be achieved.
作者
胡志新
王涛
HU Zhixin;WANG Tao(School of Mechanical and Electronic Engineering,East China University of Technology,Nanchang 330000,China)
出处
《电光与控制》
CSCD
北大核心
2022年第1期75-79,共5页
Electronics Optics & Control
基金
国家重大科学仪器设备开发专项(2018YFF01011300)
东华理工大学博士基金项目(DHBK2019173)。
关键词
双目标定
遗传算法
BP神经网络
全局最优
binocular calibration
genetic algorithm
BP neural network
global optimization
