OpenCV的相机标定在高速相机中的应用
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摘要
视频测量是近景摄影测量的一个分支,是在非接触的状态下,对处于运动状态的物体以视频或影像序列的形式瞬时记录运动物体的空间位置和状态,并通过摄影测量解析处理,获取运动物体特征点的高精度三维空间坐标,从而对运动物体的特征进行定性和定量分析,描述物体的运动轨迹和运动参数。视频测量已经逐步应用于土木工程、考古学和航空学等领域,并取得了一定的成果。相机定标是计算机三维重建不可或缺的步骤,相机定标的精度和可靠性直接影响计算机视觉系统的三维定位精度。相对于传统标定方法,本文在张正友算法的基础上结合OpenCV实现的算法。该方法使用更加方便、快捷,标定结果更加精确。
Videogrammetry is a branch of close range photogrammetry,whose goal is to deal with the objects in motion.The major advantage of the videogrammetry is to acquire the spatial location and status of the moving objects in the form of video or image sequences under the non-contact state.Furthermore,analytical photogrammetry processing method can be adopted to calculate the higher accurate 3 D spatial coordinates of the tracking targets attached on the moving objects.At last,the qualitative and quantitative analysis can be made for the moving objects,and the trajectory and motion parameters of the moving objects can also be described accurately.At present,videogrammetriy has been gradually applied in the field of civil engineering,archeology,aviation science,surgery and industrial inspection.Camera calibration is an indispensable step in computer 3 D reconstruction.The accuracy and reliability of camera calibration directly affect the 3 D positioning accuracy of computer vision system.Compared with the traditional calibration method,this paper implements the improved algorithm based on OpenCV based on ZHANG Zhengyou algorithm.The method is more convenient and quicker to use,and the calibration results are more accurate.
Videogrammetry is a branch of close range photogrammetry,whose goal is to deal with the objects in motion.The major advantage of the videogrammetry is to acquire the spatial location and status of the moving objects in the form of video or image sequences under the non-contact state.Furthermore,analytical photogrammetry processing method can be adopted to calculate the higher accurate 3 D spatial coordinates of the tracking targets attached on the moving objects.At last,the qualitative and quantitative analysis can be made for the moving objects,and the trajectory and motion parameters of the moving objects can also be described accurately.At present,videogrammetriy has been gradually applied in the field of civil engineering,archeology,aviation science,surgery and industrial inspection.Camera calibration is an indispensable step in computer 3 D reconstruction.The accuracy and reliability of camera calibration directly affect the 3 D positioning accuracy of computer vision system.Compared with the traditional calibration method,this paper implements the improved algorithm based on OpenCV based on ZHANG Zhengyou algorithm.The method is more convenient and quicker to use,and the calibration results are more accurate.
引文
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[14]陈胜勇,刘盛等.基于OpenCV的计算机视觉技术实现[M].北京:科学技术出版社,2008.
[2]和文娟.CMOS图像传感器的噪声分析及图像处理[D].湖北武汉:华中科技大学,2011.
[3]金宝智.图像传感器:CCD与CMOS的对比[J].现代电视技术,2005(5):80-81.
[4]冯文灏.近景摄影测量的控制[J].武汉测绘科技大学学报,2000,25(5):453-458
[5]马颂德,张正友.计算机视觉——计算理论与算法基础[M].北京:科学出版社,2003.
[6]David J Kruglinski,Scot Wingo.Visual C++技术内幕[M].北京:北京希望电子出版社,1999.
[7]侯俊杰.深人浅出MFC(第2版)[M].湖北武汉:华中科技大学出版社,2001.
[8]林俊义,黄常标,刘斌等.双目立体视觉摄像机标定及精度分析[J].华侨大学学报(自然版),2011,32(4):364-367.
[9]牛海涛,赵勋杰.采用棋盘格模板的摄像机标定新方法[J].红外与激光工程,2011,40(1):133-137.
[10]谢文寒,张祖勋,张剑清.一种新的基于灭点的相机标定方法[J].哈尔滨工业大学学报,2003,35(11):1384-1387.
[11]刘瑞祯,于仕琪.OpenCV教程基础篇[M].北京:北京航空航天大学出版社,2007.
[12]陈磊.计算机视觉类库OpenCV在VC中的应用[J].微计算机信息,2007,23(12):209-210.
[13]黄吉兰,楼新远.基于OpenCV的单目照相机定标的测试实践[J].铁路计算机应用,2009,18(4):47-49.
[14]陈胜勇,刘盛等.基于OpenCV的计算机视觉技术实现[M].北京:科学技术出版社,2008.