Under the assumption that all the camera intrinsic parameters have been known we focus on the calibration of camera extrinsic parameters including the relative rotation matrix R and translation vector between the camera coordinate system and the world coordinate system .

在假定摄像机内参数已标定的情况下，标定摄像机外部参数包括摄像机坐标系相对于 世界 坐标 系的旋转矩阵R和平移矢量T，即估计摄像机姿态。

Because the calibration method directly optimizes the camera rotation angles relative to the world coordinate system it ensures the orthonormal constraints as well as the precise solutions .

该标定方案直接优化摄像机相对于 世界 坐标 系的旋转角度，因此能够在获得精确解的同时，保证旋转矩阵的正交约束条件。

Firstly the thesis uses the relative rotation between two cameras to calculate the unified camera rotation relative to the unified the world coordinate system .

首先利用两两相机之间的相对旋转关系，求出每个相机针对统一 世界 坐标 系的旋转关系。

Before we reconstruct a3-dimensional ( 3D ) model of a scene from a set of2D images firstly we need to unify the world coordinate system ( WCS ) .

在一系列二维图像中重建一个场景的三维模型之前，首先需要统一多摄像机的 坐标 系。

For pinhole model for each point target two equations can be found from the relationship between image coordinate system ( ICS ) and world coordinate system ( WCS ) .

如果相机遵守针孔模型，那么每个对应点可以利用图像坐标系（ICS）和 世界 坐标 系（WCS）之间的变换关系列出2个方程。

By using matrix transform method the kinematic analysis for the mechanism is carried out and the mathematical model is established . So the transformation relationship between the camera coordinate system and the world coordinate system is confirmed .

利用矩阵变换方法进行运动学分析，建立该机构的数学模型，确定摄像机坐标系和 世界 坐标 系之间的变换关系，推导位置、速度、加速度正反解公式。

With the white line position information the robot vision system is calibrated and robot position and posture in the world coordinate system are obtained . Finally the system setup and software development method are described .

在提取白线位置后，对 嵌入式机器人视觉系统进行了标定，得到机器人在 世界 坐标 系 下的位置和姿态。论文最后介绍了嵌入式视觉机器人 实物构建过程中使用的软硬件环境及一些开发方法。

The light-plane parameters are successfully calibrated . Moreover the measurement references of both two cameras are unified into a common world coordinate system accurately . 4 .

成功地完成了左右摄像机光平面参数的标定，并将左右摄像机的测量基准统一于共同的 世界 坐标 系。

It aims to find out the rigid transformations of all range images captured from different viewpoints and then bring them into a common coordinate system i.e. the world coordinate system .

深度像配准是三维数字成像的关键一环，其目的就是寻找不同视角深度像间的空间位置转换关系，从而将这些深度像统一到同一个 世界 坐标 系内。

It has been proved in the literature that the homography from the x-y plane of the world coordinate system to the image plane can give rise two linear constraints on the camera 's intrinsic parameters .

空间 x-y 坐标平面与图像平面之间的单应矩阵可以提供关于摄像机内参数的2个线性约束。

Establish the model of monocular measurement through the geometric relationship obtain the transformation relationship between image coordinate and world coordinate system and finally achieve the obstacles of distance measurement .

通过几何关系推导法建立测距模型，获得图像坐标与 世界 坐标 系之间的转换关系，最后实现障碍物距离的测算。

The coordinate transformation matrix from the world coordinate system to the object coordinate system is derived by finding the converse matrix .

利用矩阵求逆的方法，推导出 世界 坐标 系到物坐标系的坐标变换矩阵。

At last the relatively attitude can be measured by the transformation between vehicle body coordinate system and the world coordinate system of N light points . The algorithm can be confirmed by the result of simulation .

最后利用N个光点在车体坐标系和 世界 坐标 系下的坐标转换，解出月球车的相对姿态，并给出了仿真结果。

The coordinate transformation matrix based on the direction cosine parameters from the object coordinate system to the world coordinate system is derived by vector algebra .

利用矢量代数的方法，推导出以方向余弦为参量的物坐标系到 世界 坐标 系的坐标变换矩阵；

Establishing mapping relationship between image coordinate system and the world coordinate system vehicle movement speed can be calculated .

然后，建立图像坐标系和 世界 坐标 系的映射关系，根据测速原理，计算车辆运动速度。

The relationship between image coordinate system and world coordinate system is confirmed by the calibrations of microassembly and visual systems .

通过对微装配 系统和视觉系统的标定，得到图像坐标系和 世界 坐标 系的关系。

A new method for merge of range data and texture based on calibrating two cameras in a world coordinate system is proposed .

在将两个摄像机对同一 坐标 系（ 全局 坐标 系）标定的基础上，提出了距离数据及纹理的融合方法。