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基于HEIV模型的摄像机一维标定

DOI: 10.3724/SP.J.1004.2014.00643, PP. 643-652

Keywords: 摄像机标定,一维标定物,HEIV模型,多摄像机系统,计算机视觉

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Abstract:

?多摄像机系统广泛应用于文化创意产业,其高精度标定是迫切需要解决的一个关键问题.新近出现的摄像机一维标定方法能够克服标定物自身遮挡,特别适合标定多摄像机系统.然而,现有的摄像机一维标定研究主要集中在降低一维标定物的运动约束,而标定精度较低的问题未受到应有的关注.本文提出一种基于变量含异质噪声(Heteroscedasticerror-in-variables,HEIV)模型的高精度摄像机一维标定方法.首先,推导出摄像机一维标定的计算模型;其次,利用该计算模型详细分析了一维标定中的噪声,得出摄像机一维标定可以视为一个HEIV问题的结论;最后给出了基于HEIV模型的摄像机一维标定算法.与现有的算法相比,该方法可以显著改善一维标定的精度,并且受初始值影响小,收敛速度快.实验结果验证了该方法的正确性和可行性.

References

[1]  Hammarstedt P, Sturm P, Heyden A. Degenerate cases and closed-form solutions for camera calibration with onedimensional objects. In: Proceedings of IEEE Conference on Computer Vision. Beijing, China: IEEE, 2005. 317-324
[2]  Wu F C, Hu Z Y, Zhu H J. Camera calibration with moving one-dimensional objects. Pattern Recognition, 2005, 38(5): 755-765
[3]  Wang L, Wu F C, Hu Z Y. Multi-camera calibration with one-dimensional object under general motions. In: Proceedings of IEEE Conference on Computer Vision. Rio de Janeiro, Brazil: IEEE, 2007. 1-7
[4]  Wang Liang, Wu Fu-Chao. Multi-camera calibration based on the one-dimensional object. Acta Automatica Sinica, 2007, 33(3): 225-231(王亮, 吴福朝. 基于一维标定物的多摄像机标定, 自动化学报, 2007, 33(3): 225-231)
[5]  Zhao Z J, Liu Y C, Zhang Z Y. Camera calibration with three noncollinear points under special motions. IEEE Transactions on Image Processing, 2008, 17(12): 2393-2402
[6]  Miyagawa I, Arai H, Koike H. Simple camera calibration from a single image using five points on two orthogonal 1-D objects. EEE Transactions on Image Processing, 2010, 19(6): 1528-1538
[7]  Duan Fu-Qing, Lv Ke, Zhou Ming-Quan. Central catadioptric camera calibration based on collinear space points. Acta Automatica Sinica, 2011, 37(11): 1296-1305(段福庆, 吕科, 周明全. 基于空间共线点的单光心反射折射摄像机标定, 自动化学报, 2011, 37(11): 1296-1305)
[8]  Duan F Q, Wu F C, Zhou M Q, Deng X M, Tian Y. Calibrating effective focal length for central catadioptric cameras using one space line. Pattern Recognition Letters, 2012, 33(5): 646-653
[9]  Franca J, Stemmer M R, Franca M B M, Alves E G. Revisiting Zhang's 1D calibration algorithm. Pattern Recognition, 2010, 43(3): 1180-1187
[10]  Wang L, Duan F Q. Zhang's one-dimensional calibration revisited with the heteroscedastic error-in-variables model. In: Proceedings of IEEE Conference on Image Processing. Brussels, Belgum: IEEE, 2011. 857-860
[11]  Shi K, Dong Q, Wu F C. Weighted similarity-invariant linear algorithm for camera calibration with rotating 1-D objects. IEEE Transactions on Image Processing, 2012, 21(8): 3806-3812
[12]  Cerone V, Piga D, Regruto D. Setmembership error-in-variables identification through convex relaxation techniques. IEEE Transactions on Automatic Control, 2012, 57(2): 517-522
[13]  Matei B C, Meer P. Estimation of nonlinear errors-in-variables models for computer vision application. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(10): 1537-1552
[14]  Kanatani K. Optimization techniques for geometric estimation: beyond minimization. Structural, Syntactic, and Statistical Pattern Recognition, Lecture Notes in Computer Science, 2012, 7626: 11-30
[15]  Tsai R. An efficient and accurate camera calibration technique for 3d machine vision. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Miami, USA: IEEE, 1986. 364-374
[16]  Zhang Z Y. Flexible camera calibration by viewing a plane from unknown orientations. In: Proceedings of IEEE Conference on Computer Vision. Kerkya, Greece: IEEE, 1999. 666-673
[17]  Duan F Q, Wu F C, Hu Z Y. Pose determination and plane measurement using a trapezium. Pattern Recognition Letter, 2008, 29(3): 223-231
[18]  Zhang Z Y. Camera calibration with one-dimensional objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(7): 892-899
[19]  Pollefeys M, Gool L V, Oosterlinck A. The modulus constraint: a new constraint for self-calibration. In: Proceedings of the International Conference on Pattern Recognition. Vienna, Austria, 1996. 349-353
[20]  Hartley R. In defence of the eight-point algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(6): 580-593
[21]  Soderstroma T, Wang L P, Pintelonc R, Schoukens J. Can errors-in-variables systems be identified from closed-loop experiments? Automatica, 2013, 49(2): 681-684

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