基于神经网络的双目视觉摄像机标定方法的研究
DOI:
CSTR:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TP391

基金项目:


Study on Camera Calibration for Binocular Vision Based on Neural Network
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    摄像机标定是精密视觉测量的基础,传统的双目标定位需要建立复杂的数学模型。神经网络可以有效地处理非线性映射问题,本文介绍了一种BP神经网络,可以很好地描述双目视觉中三维空间特征点坐标和2个摄像机对应像点间的非线性关系,并且为了提高网络的学习能力引入了动态因子。将神经网络标定方法与传统的常用标定方法比较,实验结果表明,基于神经网络的双目视觉标定方法能获得较高的标定精度。

    Abstract:

    An accurate camera calibration method is required to achieve precise visual measurements,and traditional binocular calibration methods involve complicated mathematical models. As neural networks are effective for dealing with non-linear mapping, in the paper a BP neural network is proposed and implemented,which could satisfactorily describes the non-linear relations between 3-D characteristic points and their corresponding stereo images in the binocular vision. In order to improve the learning ability of the network,a dynamic gene is also introduced to the BP algorithm. Compared with traditional calibration methods, experimental results show that the proposed binocular calibration method based on neural network could obtain high accuracy.

    参考文献
    相似文献
    引证文献
引用本文

崔彦平 林玉池 张晓玲.基于神经网络的双目视觉摄像机标定方法的研究[J].光电子激光,2005,(9):1097~1100

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2005-01-07
  • 最后修改日期:2005-06-09
  • 录用日期:
  • 在线发布日期:
  • 出版日期:
文章二维码