世界坐标系

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。

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 .

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。

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 .

粒子在世界坐标系内的开始速度，沿着X，Y和Z轴。

The starting speed of particles in world space , along X , Y , and Z.

在世界坐标系中，机器人x-y运动为视觉伺服控制，而机器人的z运动为位置伺服控制。

The x-y motion of robot in world frame was vision control while the z motion of robot is position control .

利用摄像机定标获得的摄像机外参数即旋转矩阵R与平移向量t，将不同摄像机拍摄到的物体不同侧面，拼接到同一世界坐标系下。

Extrinsic parameters ( rotation matrix Rand translation vectort ) derived from camera calibration were used to combine multiple views from different cameras into complete information on the same system of co ordinates .

针对各VRML造型在其局部坐标系中创建，采用变换矩阵实现了造型从局部坐标系下到世界坐标系下的坐标变换。

Because each model in VRML is created in local coordinate system , inconvenient to handle them uniformly , this paper infers a universal formula to transform model coordinates from UCS to 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。

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 ) .

这是粒子在世界坐标系中的尺寸。

This is particle 's size in meters in world space .

机器人手眼关系、基坐标系和世界坐标系关系的同时标定

Simultaneous calibration for relationship of robot hand-eye , base coordinates and world coordinates

用矩阵变换来实现从世界坐标系的运动到机器人关节坐标系运动的映照。

A transformation was used to map the motion in world frame to robot joint frame .

基于方向余弦参量的物坐标系与世界坐标系间的坐标变换

Coordinate Transformation Based on Direction Cosine Parameters between the Object Coordinate System and the Word Coordinate System

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。

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

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。

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

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。

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

该模型将监控摄像头拍摄到的视频序列中车辆的位置恢复到现实世界坐标系中，从而可以进行准确的车速检测。

This model enables us to estimate the real world position of the vehicles directly from a video sequence taken by a surveillance camera .

根据计算机视觉成像原理，利用三维点到二维点的投影关系，可以计算出摄像机相对世界坐标系的平移和旋转参数。

Using the relationship of the projective transformation between 3d points and 2d points , the translation and the rotation angle can be computed .

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。

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

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；

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 .

将机器鱼和传感器局部坐标系选为与三维仿真系统的世界坐标系一致，简化了虚拟射线法探测障碍物时坐标变换的计算难度。

The difficulty of coordinate transformation calculation is simplified by selecting robot fish and sensor local coordinates which are the same with world coordinates of 3D simulation system .

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。

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 .

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。

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 .

增强现实系统中注册的根本问题是世界坐标系，摄像机坐标系，图像平面坐标系，象素平面坐标系之间的坐标转换问题。

The fundamental problem of the registration of the AR is the matrics transformation between the world coordinate , camera coordinate , image plane coordinate and pixel plane coordinate .

这种情况下不需要标定摄像机在世界坐标系的位置，相对的对于世界坐标系的旋转矩阵和平移矩阵也不需要。

In this instance , the location of camera in the world coordinates is unnecessary to calibrated , and the rotary matrix and horizontal movable matrix is needless too .

在此基础上提出了一种恢复目标物体在世界坐标系中的三维坐标的方法，为实现对目标物体位置的快速判断和跟踪提供了有力的前提。

Based on it , a new method is presented to obtain the world coordinate of target point , which provides much precondition for locating and tracing the object quickly .

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。

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 .

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 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 .

本文研究了高速公路自主驾驶汽车车道检测问题，实现了透视道路图像到世界坐标系的逆投影，提出并实现了在投影后图像中进行道路标志线检测的算法。

This dissertation has researched on Lane Detection technology for AHV ( Autonomous Highway Vehicle ), implemented the inverse perspective projection from perspective road image to world coordinates and proposed Lane Detection arithmetic for projected image .

建立了移动机器人的摄象机模型，从而完成了世界坐标系到摄象机坐标系的转换，使障碍物信息成功地转换到摄像机坐标系，完成了不同坐标系之间的统一。

The model of camera and the conversion from obstacle image coordinate into the world coordinate is completed , which the information of obstacle is converted into camera coordinate . therefore the different coordinate are unified .

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。

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 .

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。

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 .