中心折反射相机标定方法综述

J4 ›› 2014, Vol. 36 ›› Issue (05): 951-956.

中心折反射相机标定方法综述

张艳,赵丽娜,胡万宝

（北京化工大学理学院，北京 100029）

收稿日期:2012-09-24 修回日期:2013-03-12 出版日期:2014-05-25 发布日期:2014-05-25
基金资助:
国家自然科学基金天元基金资助项目（10926187）；中央高校基本科研业务费专项资金资助项目（ZZ1019）；国家自然科学青年基金资助项目（11301021）

Review of central catadioptric camera calibration methods

ZHANG Yan,ZHAO Lina,HU Wanbao

(College of Science,Beijing University of Chemical Technology,Beijing 100029,China)

Received:2012-09-24 Revised:2013-03-12 Online:2014-05-25 Published:2014-05-25

摘要/Abstract

摘要：

近十几年来，计算机视觉越来越受研究者们的欢迎，特别是全景相机由于其具有较大的视场而被广泛应用到许多领域，包括视频监控、机器人导航、电视电话会议、场景重建以及虚拟现实等。摄像机标定是从二维图像获得三维信息必不可少的一步，摄像机标定结果的好坏直接决定着三维重建结果以及其它计算机视觉应用效果的好坏，所以，研究摄像机的标定方法具有重要的理论研究意义和重要的实际应用价值。这里将2000年到2012年折反射相机标定方法按照标定像的不同分为五大类：基于线的标定、基于二维标定块标定、基于三维点的标定、基于球的标定和自标定，且简要分析其优缺点。

关键词: 球面模型, 折反射, 相机标定

Abstract:

In recent dozen years,computer vision becomes more popular,in which omnidirectional camera has a larger field of view (FOV) and widely been used in many fields,such as:robot navigation,visual surveillance,virtual reality, threedimensional reconstruction, and so on.Camera calibration is an essential step to obtain threedimensional geometric information from a twodimensional image.Camera calibration results directly decide the results of 3-D reconstruction and other computer vision application effect.Hence,the study of such camera calibration method has important theoretical significance and practical applications.The paper classifies these methods from 2000 to 2012,by means of the difference calibration blocks,into five categories:calibration based on line;calibration based on two-dimensional calibration block;calibration based on three-dimensional point;calibration based on balls;selfcalibration. And these methods’advantages and disadvantages are analyzed.

Key words: spherical model;catadioptric;camera calibration

张艳,赵丽娜,胡万宝. 中心折反射相机标定方法综述[J]. J4, 2014, 36(05): 951-956.

ZHANG Yan,ZHAO Lina,HU Wanbao. Review of central catadioptric camera calibration methods [J]. J4, 2014, 36(05): 951-956.

参考文献

［1］Baker S, Nayer S. A theory of singleviewpoint catadioptric image formation［J］. International Journal of Computer Vision, 1999, 35(2):175196.
［2］Geyer C, Daniilidis K. Catadioptric projective geometry ［J］. International Journal of Computer Vision, 2001, 45(3):223243.
［3］Svoboda T,Pajdla T.Epipolar geometry for central catadioptric cameras ［J］. International Journal of Computer Vision, 2002, 49 (1):2337.
［4］Geyer C, Daniilidis K. A unifying theory for central panoramic systems and practical applications［C］∥Proc of the 6th European Conference on Computer Vision Part II, 2000:445461.
［5］Ying Xianghua, Hu Zhanyi. Catadioptric camera calibration using geometric invariants［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26 (10):12601271.
［6］Barreto J P,Araujo H.Issues on the geometry of central catadioptric image formation［C］∥Proc of IEEE Conference on Computer Vision and Pattern Recognition, 2001:422427.
［7］Deng Xiaoming, Wu Fuchao, Wu Yihong. An easy calibration method for central catadioptric cameras［J］. Acta Automatic Sinica, 2007,33(8):801808.
［8］Duan Huixian, Wu Yihong. A calibration method for paracatadioptric camera from sphere images［J］. Pattern Recognition Letters, 2012, 33(6):677684.
［9］Puig L, Bermudez J, Sturm P, et al. Calibration of omnidirectional cameras in practice:A comparison of methods ［J］. Computer Vision and Image Understanding, 2012,116(1):120137.
［10］Geyer C, Daniilidis K. Paracatadioptric camera calibration［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(5):687695.
［11］Barreto J P, Araujo H. Geometric properties of central catadioptric line images and their application in calibration［J］. Pattern Analysis and Machine Intelligence, 2005, 27(8):13271333.
［12］Ying Xianghua, Zha Hongbin. Simultaneously calibrating catadioptric camera and detecting line features using Hough transformation［C］∥Proc of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005:13431348.
［13］Wu Fuchao, Duan Fuqing, Hu Zhanyi, et al. A new linear algorithm for calibrating central catadioptric cameras ［J］. Pattern Recognition, 2008,41(10):31663172.
［14］Barreto J P, Araujo H. Fitting conics to paracatadioptric projections of lines［J］. Computer Vision and Image Understanding, 2006, 101(3):151165.
［15］Sturm P, Barreto J. General imaging geometry for central catadioptric cameras ［C］∥Proc of European Conference on Computer Vision, 2008:609622.
［16］Wu Yihong, Zhu Haijiang, Hu Zhanyi, et al. Camera calibration from the quasiaffine invariance of two parallel circles［C］∥Proc of European Conference on Computer Vision, 2004:190202.
［17］Gasparini S, Sturm P, Barreto J P. Planebased calibration of central catadioptric cameras ［C］∥Proc of International Conference on Computer Vision, 2009:11951202.
［18］Aliaga D G. Accurate catadioptric calibration for realtime pose estimation in roomsize environments［C］∥Proc of the 8th International Conference on Computer Vision, 2001:127134.
［19］Vasseur P, Mouaddib E. Central catadioptric line detection［C］∥Proc of British Machine Vision Conference, 2004:1.
［20］Wu Yihong, Hu Zhanyi. Geometric invariants and applications under catadioptric camera model ［C］∥Proc of International Conference on Computer Vision, 2005:15471554.
［21］Deng Xiaoming, Wu Fuchao, Duan Fuqing, et al. Catadioptric camera calibration with onedimensional objects［J］. Chinese Journal of Computers,2007,30(5):737747.(in Chinese)
［22］Puig L,Bastanlar Y,Sturm P,et al.Calibration of central catadioptric cameras Using a DLTLike approach［J］. International Journal of Computer Vision, 2011, 93(1):101114.
［23］Ying Xianghua,Zha Hongbin.Identical projective geometric properties of central catadioptric lines images and sphere images with applications to calibration［J］. International Journal of Computer Vision, 2008, 78(1):89105.
［24］Kang S B. Catadioptric selfcalibration ［C］∥Proc of the IEEE Conference on Computer Vision and Patten Recognition, 2000:201207.
［25］Ramalingam S, Sturm P, Lodha S K. Generic selfcalibration of central cameras［J］. Computer Vision and Image Understanding, 2010, 114(2):210219.
［26］Espuny F, Gil J B. Generic selfcalibration of central cameras from two rotational flows［J］. International Journal of Computer Vision, 2011, 91(2):131145.
附中文参考文献：
［21］邓小明,吴福朝,段福庆,等,基于一维标定物的反射折射摄像机标定方法［J］.计算机学报，2007,30(5):737747.

[1]	姚隆兴, 韩江涛, 张志毅. Tsai氏相机平面标定算法的一种解析改进[J]. 计算机工程与科学, 2022, 44(11): 1976-1984.
[2]	孟勃，刘雪君. 一种自动、快速的Kinect标定方法[J]. J4, 2016, 38(06): 1193-1199.
[3]	章权兵，孙庆，王磊，程鸿. 旋转曲面的度量重构[J]. J4, 2013, 35(8): 109-113.
[4]	刘碧霞1,2，李绍滋1,3，郭锋1,3，苏松志1,3. 一种简单快速的相机标定新方法[J]. J4, 2011, 33(1): 88-93.
[5]	易大江王浩贾坤丁文霞郭桂蓉. 基于球面模型的GPS／DR组合导航系统研究[J]. J4, 2008, 30(6): 121-124.
[6]	徐玮王炜张茂军吴玲达. 一种基于凸曲面反射镜的柱面全景图像无缝快速生成系统[J]. J4, 2006, 28(11): 33-36.