铁路运行环境下的车载相机姿态估计
于欣妍, 罗四维, 许廷发, 王亮, 王胜春. 铁路运行环境下的车载相机姿态估计[J]. 光学技术, 2015, 41(3): 197.
YU Xinyan, LUO Siwei, XU Tingfa, WANG Liang, WANG Shengchun. Attitude estimation of the train-borne camera from the railway-environment[J]. Optical Technique, 2015, 41(3): 197.
[1] 侯卫星.0号高速综合检测列车[M].北京: 中国铁道出版社, 2010.
Hou W X. No. 0 high-speed integrative inspection train [M]. China Railway Press, 2010.
[2] 中国铁道科学研究院.高速综合检测列车技术交流总结[R]. 2006.
Railway Science Research Institute of China. Technical summary of high-speed integrative inspection train china[R]. 2006.
[3] Chen S E, Quicktimevr. An image-based approach to environment navigation[C]∥ Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, ACM, 1995: 29-38.
[4] Li Q, Ren S. A visual detection system for rail surface defects, systems, man, and cybernetics, Part C: Applications and reviews[J]. IEEETransactions on, 2012, 42(6): 1531-1542.
[5] Deutschl E, Gasser C, Niel A, et al. Defect detection on rail surfaces by a vision based system[C]∥Intelligent Vehicles Symposium, IEEE, 2004: 507-511.
[6] Espino J C, Stanciulescu B. Turnout detection and classification using a modified hog and template matching, intelligent transportation systems[C]//2013 the 16th International IEEE Annual Conference on IEEE, 2013: 2045-2050.
[7] Wang S, Zheng J Y, Luo S. Route panorama acquisition and rendering for high-speed railway monitoring[C]∥ Multimedia and Expo (ICME), 2013 IEEE International Conference , 2013: 1-6.
[8] Alippi C, Casagrande E, Scotti F, et al. Composite real-time image processing for railways track profile measurement[J]. IEEE Transactions on Instrumentation and Measurement, 2000,49(3): 559-564.
[9] Horn B K, Negahdaripour S. Direct passive navigation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1987, (1): 168-176.
[10] Horn B K, Fang Y, Masaki I. Time to contact relative to a planar surface, intelligent vehicles symposium[C]. IEEE, 2007: 68-74.
[11] Thrun S, et al. Camera calibration[M]. Stanford CS223B Computer Vision, 2003.
[12] Tsai R Y. An efficient and accurate camera calibration technique for 3D machine vision[C].Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Miami Beach FL, 1986: 364-374.
[13] 邱茂林, 马颂德, 李毅. 计算机视觉中相机标定综述[J]. 自动化学报, 2000, 26(1): 43-55.
Qiu M L, Ma S D, Li Y. Overview of camera calibration for computer vision[J]. ACTA Automatica Sinica, 2000,26(1): 43-55.
[14] 徐杰.机器视觉中摄像机标定Tsai两步法的分析与改进[J]. 计算机工程与科学. 2010,32(04),45-48.
Xu J. Analyzing and improving the Tsai camera calibration method in machine vision[J]. Computer Engineering & Science, 2010,32(04): 45-48.
[15] 张吴明,钟约先. 基于改进差分进化算法的相机标定研究[J]. 光学技术. 2004,30(6): 720-723.
ZhangW M, ZhongY X. Camera calibration based on improved differential evolution algorithm[J]. Optical Technique, 2004, 30(6): 720-723.
[16] 陈钊,郭永彩. 体视2D-3cPIV相机标定方法研究[J]. 光学技术 2007,33(6): 881-888.
[17] Willert C E. Assessment of camera models f or use in planar velocimetry calibration[J].Experiments in Fluids ,2006 , 41 (2): 135-143.
[18] Roger Y. Tsai a versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV camera and lenses[J] .IEEE Journal of Robotics and Automatuon , 1987 ,RA-3(4): 323-344 .
[19] Zhang Z Y. Aflexible new technique f or camera calib ration[ J] .IEEE Transact ions on Pattern Analysis and Machine Intelligence, 2000 , 22(11): 1330-1334.
[20] Wieneke B. Stereo-PIV using self-calibration on particle images[ J] .Experiments in Fluids , 2005 , 39(2): 267-280.
[21] 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,1998.
Ma S D, Zhang Z Y. Computation theory of computer vision and algorithms[M].Beijing: Science Press,1998.
[22] Westeon P, Ling C, Roberts C, et al. Monitoring vertical track irregularity from in-service railway vehicles[J]. Proceedings of the institution of mechanical engineers, Part F: Journal of Rail and Rapid Transit, 2007,221(1): 75-88.
[23] Strang G. Introduction to linear algebra[M]. Wellesley Cambridge Press, 2003.
[24] Horn B K P. Robot vision[M]. The MIT Press, 1986.
[25] Caprile B, Torre V. Using vanishing points for camera calibration[J].International Journal of Computer Vision, 1990,4(2): 127-139.
[26] Xu Y, Oh S, Hoogs A. A minimum error vanishing point detection approach for uncalibrated monocular images of man-made environments[C]∥Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference, 2013: 1376-1383.
[27] Duda R O, Hart P E. Use of the hough transformation to detect lines and curves in pictures[J]. Communicati- ons of Association for Computing Machinery. 1972,15(1): 11-15.
[28] von Gioi R G, Jakubowicz J, Morel J M, et al. Lsd: A fast line segment detector with a false detection control,pattern analysis andmachine intelligence[J]. IEEE Trans, 2010,32(4): 722-732.
[29] Albert A E, Albert A. Regression and the Moore-Penrose pseudo inverse[M ]. Academic Press NewYork, 1972, 3.
[30] Strang G. Computational science and engineering[M].Wellesley Cambridge Press, 2007.
于欣妍, 罗四维, 许廷发, 王亮, 王胜春. 铁路运行环境下的车载相机姿态估计[J]. 光学技术, 2015, 41(3): 197. YU Xinyan, LUO Siwei, XU Tingfa, WANG Liang, WANG Shengchun. Attitude estimation of the train-borne camera from the railway-environment[J]. Optical Technique, 2015, 41(3): 197.