基于普吕克直线的多线结构光视觉传感器标定方法

针对多线结构光系统的快速标定,提出了一种基于普吕克直线的标定方法。传统的线结构光标定方法大多以单点的形式进行提取和坐标系转换,从而获得平面方程。然而单点数量较多会导致操作复杂,不适用于多线结构光的标定。为了解决这个问题,提出了一种新的标定方法,该方法在标定过程中全部采用普吕克矩阵的形式,而不是直接使用点特征。该方法有利于在摄像机坐标系下快速准确地获得光平面方程。同时设计了一种与该方法相对应的用于标定多线结构光的平面标定靶标。为了将一般直线转换为普吕克直线,将图像平面维度延展,定义了一个新的图像空间。为了对普吕克直线的坐标系进行转换,重新表达了基于普吕克直线的透视投影模型。基于普吕克空间中直线与平面的性质,对多条结构光线的普吕克矩阵进行合并即可高效地构造出线性的矩阵方程,从而进一步拟合出结构光平面方程。实验验证了所提方法并证明了校准精度的显著提高,当测试距离为1.8 m时,测量得到的三维点的RMS误差在0.08 mm之内。

Calibration method for multi-line structured light vision sensor based on Plücker line

For the rapid calibration of multi-line structured light system,a method based on Plücker line was proposed.Most of the conventional line-structured light calibration methods extract the feature points and transform the coordinates of points to obtain the plane equation.However,a large number of points lead to complicated operation which is not suitable for the application scenarios of multi-line structured light.To solve this issue,a new calibration method was proposed that applied the form of Plücker matrix throughout the whole calibration process,instead of using the point characteristics directly.The advantage of this method is that the light plane equation can be obtained quickly and accurately in the camera coordinate frame.Correspondingly a planar target particularly for calibrating multi-line structured light was also designed.The regular lines were transformed into Plücker lines by extending the two-dimensional image plane and defining a new image space.To transform the coordinate frame of Plücker lines,the perspective projection mathematical model was re-expressed based on the Plücker matrix.According to the properties of the line and plane in the Plücker space,a linear matrix equation was efficiently constructed by combining the Plücker matrices of several coplanar lines so that the line-structured light plane equation could be furtherly solved.The experiments performed validate the proposed method and demonstrate the significant improvement in the calibration accuracy,when the test distance is 1.8 m,the root mean square(RMS)error of the three-dimensional point is within 0.08 mm.