期刊文献+

采用双相机结构光三维测量技术解决遮挡问题 被引量:1

Resolving Occlusion Problems by Using 3D Light Measurement System with Dual Camera
下载PDF
导出
摘要 针对单目结构光投影三维视觉测量系统固有的相机遮挡问题,给出了基于相机—投影仪—相机系统模型的结构光三维测量方案,并阐述了测量系统的测量原理和实现方法。系统建模时将相机—投影—相机系统看作是两个独立的相机—投影仪三维视觉测量系统,在分别得到被测对象的三维数据后,通过采用全局坐标统一方法得到同一空间坐标系下的三维点坐标。该方法可以得到较高精度的全局测量结果,重复测量相对误差约0.2%。 To overcome the well-known inherent problem of the occlusion caused by single-camera-projector system,a three-dimensional measurement method based on camera-projector-camera structured light system is proposed. The system measurement theory and implementation method are detailed. In system modeling,the camera-projection-camera system is considered as two independent camera-projector units. After the two sets of point cloud data,these two independent systems are acquired respectively,the high accuracy measurement point cloud data is obtained in the same spatial coordinate system by using the introduced system calibration methods and coordinate system unification techniques. The experimental results show that the method's performance and effectiveness and the relative measurement error is about 0. 2%.
作者 彭权 卢荣胜 穆文娟 Peng Quan;Lu Rongsheng;Mu Wenjuan
机构地区 合肥工业大学
出处 《工具技术》 2018年第3期122-125,共4页 Tool Engineering
基金 国家重大科学仪器设备开发专项(2013YQ220749)
关键词 三维立体视觉 编码结构光 标定 坐标统一 three-dimension stereo vision coded-structured light calibration coordinate system unification
  • 相关文献

参考文献1

二级参考文献10

  • 1Anwar /4, Din I, Kang P. Projector calibration for 3D scanning using virtual target images. International Journal of Precision Engineering & Manufacturing, 2012; 13(1 ) :125--131.
  • 2Kimura M, Mochimaru M, Kanade T. Projector calibration using ar- bitrary planes and calibrated camera. CVPR, IEEE Computer Society Conferen~e on Computer Vision and Patten~ Recognition. Minneapo- lis,USA. 2007:1--2.
  • 3Mosnier J, Berry F, Air-Aider O. A new method for projeclor calibra- tion based on visual servning. IAPR Conference on Machine Vision Application. Yokohama ,Japan, 2009:25--29.
  • 4Moreno D, Taubin G. Simple, accurate, and rubust projector-camera calibration. 2012 Second International Conference on 31) Imaging, Modeling, Processing, Visualization & Transmission. IEEE Computer Society. Washington, DC, USA. 2012:464---471.
  • 5Nayar, Shree K, KrishnaJ1, et al. Fast separation of dire('/and global components .f a scene using high frequency illumination. ACM Trans- actions On Graphics, 2006 ; 25 ( 3 ) :935---944.
  • 6Xu Y, Aliaga D G. Robust pixel classification for 3D modeling with structured light. In : Proceedings of Graphics Interface, 2007:233-- 240.
  • 7李中伟,史玉升,钟凯,王从军.结构光测量技术中的投影仪标定算法[J].光学学报,2009,29(11):3061-3065. 被引量:46
  • 8曾令虎,刘鹏.摄像机标定的研究[J].武汉工业学院学报,2011,30(3):47-53. 被引量:7
  • 9谢德浩,全燕鸣.结构光焊缝视觉检测系统中投影仪标定法[J].电焊机,2013,43(5):101-104. 被引量:4
  • 10刘顺涛,骆华芬,陈雪梅,徐静.结构光测量系统的标定方法综述[J].激光技术,2015,39(2):252-258. 被引量:24

共引文献3

同被引文献10

引证文献1

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部