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基于线结构光参考平面的多摄像机标定方法研究
引用本文:占栋,肖建.基于线结构光参考平面的多摄像机标定方法研究[J].仪器仪表学报,2015,36(9):2030-2036.
作者姓名:占栋  肖建
作者单位:西南交通大学电气工程学院成都610031
基金项目:国家自然科学基金(61134001)、国家自然科学基金(51177137)、国家自然科学基金(U1234203)、国家高技术研究发展计划(863计划)子课题(2011AA11A102)、西南交通大学博士创新基金项目资助
摘    要:多摄像机视觉测量系统中不同视觉传感器空间分布广,无公共视角,现场标定十分困难。针对多摄像机标定问题,研究了一种基于线结构光参考平面的灵活标定方法。标定过程中,以空间中同时覆盖相邻摄像机视角的结构光平面作为标定参考基准,在不同摄像机视角中,自由移动平面靶标多次,确保每次移动后靶标与结构光相交,并能在各自摄像机中清晰成像,摄像机拍摄靶标图像。提取靶标图像中角点坐标、激光光条特征点坐标。借助靶标平面与摄像机坐标系外部参数矩阵,求解激光光条特征点在对应摄像机坐标系中坐标。通过结构光基准平面内,不同摄像机坐标系中至少3组非共线特征点坐标信息,求解相邻摄像机外部参数。分别进行标定试验和精度验证试验,试验结果表明该方法切实可行。

关 键 词:机器视觉  标定  参考平面  多摄像机  线结构光

Study on the flexible multiple camera calibration approach based on the reference plane emitted by line structured light
Zhan Dong,Xiao Jian.Study on the flexible multiple camera calibration approach based on the reference plane emitted by line structured light[J].Chinese Journal of Scientific Instrument,2015,36(9):2030-2036.
Authors:Zhan Dong  Xiao Jian
Affiliation:School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Abstract:In multiple camera visual measurement system, various visual sensors have the features of wide spatial distribution and no common field of view (FOV), which makes the field global calibration of the multiple cameras extremely difficult. Aiming at the multiple camera calibration problem, a flexible multiple camera calibration approach based on the reference plane emitted by the line structured light source is investigated. In the calibration process, the structured light plane that simultaneously cover the FOV of the adjacent cameras in the space is taken as the calibration reference plane. In the FOV of different cameras, the planar target is freely moved several times. At each planar target spatial position, the planar target should intersect with the reference plane and format a laser strip on the target plane, and guarantee that the image can be clearly captured by each camera. Then, the image extraction algorithm is employed to determine the coordinates of the image corners and the feature points of the corresponding laser stripes. With the help of the extrinsic parameter matrix between the target plane and camera coordinate frame, the coordinates of the feature points of different laser stripes reference to corresponding camera coordinate frame are computed. Then, the coordinates of at least three non collinear feature points on the reference plane in different camera coordinate frames are used to calculate the extrinsic parameters of the neighboring cameras. The dedicated experiments consisting of camera calibration and accuracy verification were conducted respectively, and the experiment results demonstrate the effectiveness of the proposed approach.
Keywords:machine vision  calibration  reference plane  multiple camera  line structured light
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