基于投影仪和摄像机的结构光视觉标定方法

计算机工程与应用 ›› 2014, Vol. 50 ›› Issue (24): 168-172.

基于投影仪和摄像机的结构光视觉标定方法

刘俸材1，2，李爱迪1，2，马泽忠1，2

1.重庆市国土资源和土地房屋勘测规划院，重庆 400020
2.国家遥感应用工程技术研究中心重庆研究中心，重庆 400020

出版日期:2014-12-15 发布日期:2014-12-12

Method for calibration of structured-light vision based on projector and camera

LIU Fengcai1，2，LI Aidi1，2，MA Zezhong1，2

1.Chongqing Institute of Surveying and Planning for Land Resource and Buildings, Chongqing 400020, China
2.Chongqing Research Center, National Engineering Technology Research Center for Remote Sensing Applications, Chongqing 400020, China

Online:2014-12-15 Published:2014-12-12

摘要/Abstract

摘要： 为实现基于投影仪和摄像机的结构光视觉系统连续扫描，需要计算投影仪投影的任意光平面与摄像机图像平面的空间位置关系，进而需要求取摄像机光心与投影仪光心之间的相对位置关系。求取摄像机的内参数，在标定板上选取四个角点作为特征点并利用摄像机内参数求取该四个特征点的外参数，从而知道四个特征点在摄像机坐标系中的坐标。利用投影仪自身参数求解特征点在投影仪坐标系中的坐标，从而计算出摄像机光心与投影仪光心之间的相对位置关系，实现结构光视觉标定。利用标定后的视觉系统，对标定板上的角点距离进行测量，最大相对误差为0.277%，表明该标定算法可以应用于基于投影仪和摄像机的结构光视觉系统。

关键词: 结构光视觉, 标定方法, 摄像机标定, 三维恢复

Abstract: To get continuous scanning of the structured-light vision system which is based on the projector and camera, it is needed to calculate the space position relationship between any light plane of the projector and image plane of the camera. Also the relative position between optical centre of camera and projector requires to be obtained. This paper settles the camera intrinsic parameters. Four corner points in the calibration board are used as characteristic points, also their extrinsic parameters are computed by using the intrinsic parameters of the camera. So coordinates of four characteristic points in the camera coordinate system can be found. The coordinates of the four characteristic points in the projector coordinate system can be computed by using the parameters of the projector itself. Thus, the relative position between optical center of camera and projector is obtained. That’s the process of calibration of structured-light based on camera and projector. The angular distance between corner points on calibration board is measured by structured-light vision system that has been calibrated above. The maximum relative error is 0.277%, which indicates that the calibration algorithm can be used in structure-light vision system based on projector and camera.

Key words: structured-light vision, calibration method, camera calibration, 3D recovery

刘俸材1，2，李爱迪1，2，马泽忠1，2. 基于投影仪和摄像机的结构光视觉标定方法[J]. 计算机工程与应用, 2014, 50(24): 168-172.

LIU Fengcai1，2，LI Aidi1，2，MA Zezhong1，2. Method for calibration of structured-light vision based on projector and camera[J]. Computer Engineering and Applications, 2014, 50(24): 168-172.

[1]	孙博轩1，魏志光2，梁军2，肖琳3. 用于单目视觉的路径失真矫正系统设计与实现[J]. 计算机工程与应用, 2014, 50(14): 180-184.
[2]	李一波，申晓玲，刘艳梅，王新星. 采用计算机视觉进行室内飞艇定位的方法研究[J]. 计算机工程与应用, 2013, 49(9): 176-179.
[3]	潘亚宾，刘国栋. 直线运动摄像机在线动态标定[J]. 计算机工程与应用, 2012, 48(2): 188-190.
[4]	郑俊，龚声蓉，刘纯平. 一种使用校正模板的非线性摄像机标定方法[J]. 计算机工程与应用, 2011, 47(31): 192-196.
[5]	郭阳，张祥德. 未标定的非共面P4P解数的研究[J]. 计算机工程与应用, 2011, 47(27): 168-171.
[6]	廉小磊，贺利乐，张颖. 基于粒子群算法的双目立体视觉系统标定[J]. 计算机工程与应用, 2011, 47(24): 202-204.
[7]	芮挺，马光彦，廖明，甄树新. 模拟退火粒子群优化双目立体测量方法[J]. 计算机工程与应用, 2011, 47(22): 160-163.
[8]	毛亮，薛月菊，邹湘军，刘国英，卢启福. 基于Moore-Penrose广义逆修正的摄像机标定方法[J]. 计算机工程与应用, 2011, 47(20): 194-196.
[9]	王磊，章权兵. 单轴运动下未标定图像序列的度量重构[J]. 计算机工程与应用, 2011, 47(16): 179-181.
[10]	郁钱，孙俊，须文波. 量子粒子群优化算法在摄像机标定中的应用[J]. 计算机工程与应用, 2011, 47(14): 200-203.
[11]	王靖韬，侯振杰. 传统相机标定方式的自动标定方法[J]. 计算机工程与应用, 2010, 46(35): 205-208.
[12]	崔岸，何大鹏，王丹. 空间圆几何参数视觉测量方法研究[J]. 计算机工程与应用, 2010, 46(32): 55-58.
[13]	韩晓乐，蔡宇，董天，徐明飞，张树功. 由共面圆确定摄像机参数的线性方法[J]. 计算机工程与应用, 2010, 46(1): 160-163.
[14]	吴刚，唐振民. B双空间几何中基于消隐点的摄像机标定[J]. 计算机工程与应用, 2009, 45(24): 4-6.
[15]	陈应松^1，2，肖世德²，王文玺²，林静²，张卫华³. 自主导航移动机器人视觉系统的一种标定方法[J]. 计算机工程与应用, 2009, 45(23): 190-192.