基于GA-BP神经网络的双摄像机位姿视觉调节方法

Method for Visual Adjustment of Two-camera Position Based on GA-BP Neural Network

文中提出了双摄像机模组位姿调节参数计算的GA优化BP神经网络模型,根据目标模板上的特征点在双摄像机上的成像坐标,计算两个摄像机之间的位姿偏离参数。为弥补BP神经网络的不足,采用GA算法对BP神经网络进行了优化。利用训练样本数据集对所提出的模型进行了训练,并利用测试样本数据集对模型进行了测试;最后将训练好的模型用于双摄像机模组位姿调节的实际生产中。实际应用结果表明,基于所提出的方法设计的双摄像机模组位姿调节装置,调节精度和调节时间都能满足实际生产的要求。

The target template was designed and the BP neural network model was proposed,which can calculate the position deviation parameter between the two cameras according to the image coordinates of the feature points on the target template on the dual camera.GA algorithm is used to optimize BP neural network to compensate the shortco-mings.The training sample data set is used to train the proposed model,and the model is tested with the test sample data set,and finally the training model is used for the actual production of the two-camera module.The actual application results show that the calibration precision and time can meet the requirements of actual production based on the proposed method.