A New Method for Coplanar Camera Calibration Based on Neural Network

摘要：

As an essential step of 3D reconstruction, research on the camera calibration methods has great important significance of theoretical study and practical value. In this paper, a new simply, flexible and more accurate coplanar camera calibration method is proposed based on neural network. This method only requires a coplanar target and without camera motion. The neural network is used to learn the relationships between the image information and the 3D information to emend aberrance of camera, and it neither requires the inner and outer parameters of the camera and any prior knowledge of the parameters. The experimental results of image simulation show that the proposed method is correct and effective.

关键词： camera calibration coplanar target aberrance emendation neural network

作者: Chen Xiaobo Guo Haifeng Yang Yinghua Qin Shukai

作者单位: College of Information Science and Engineering Northeastern University Shenyang, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 617-621

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）