基于旋转对称三角测量视觉传感器的高分辨率三维信息获取技术研究
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摘要
信息获取是信息科学的重要分支，是传统传感技术与其他多学科的发展与交叉融合的产物，表现为信息获取的高精度、高速度、集成化、智能化等特性。三维信息的获取是信息获取的重要组成部分，研究如何获取物体在三维空间中表现出的几何结构和尺度信息，主要是在传统的二维投影尺寸上增加深度信息，更全面真实的表示被测物体。随着科技水平的不断发展，三维信息的获取在科学研究和工业生产中体现出越来越重要的地位。
本文以三维信息获取技术为主线，针对集成视觉系统的旋转对称三角位移传感器(RST Rotationaly Symmetric Triangulation)，从信息获取的传感器融合、有效性、物理极限和测量效率等角度，研究了高分辨率三维信息获取技术。主要工作包括：
1研究了旋转对称型激光三角位移传感器(RST)与视觉测量系统的集成。给出了传感器的原理与设计，实现了多传感器在物理层上的融合。
2研究了RST传感器在安装和调整时引入的系统误差与补偿技术。提出了该传感器的几何光学测量模型；重点研究了由于投射激光偏离旋转轴和图像传感器的倾斜等因素造成系统旋转对称性下降而引起的误差因素；针对旋转对称性下降情况下的圆环缺失，提出了基于神经网络的误差补偿方法。给出了该传感器实验样机位移测量的不确定度。
3研究了RST位移测量的不确定度极限。重点研究了RST中的激光散斑现象，从散斑统计学的角度，首次推导了激光散斑引起的旋转对称三角法位移测量不确定度的极限，结果表明在光学粗糙表面上，该极限由投射激光波长，光学系统入瞳对投射光斑所张的立体角，以及光学系统主光轴与旋转轴的夹角确定；这一结论同样适用于其他变形成像(anamorphic)的激光三角法。
4基于RST的工作方式，研究了利用集成视觉系统的扫描移动来获得被测物体的低分辨率三维信息的方法。针对近景摄影测量中被测物缺乏足够的纹理细节问题，提出了一种基于对称多基线图像序列的匹配方法；利用亚象素匹配提高其精度，并获得一个连续的三维边缘；仅针对物体的边缘特征进行匹配，从而提高了三维信息获取的速度和鲁棒性。
5研究了三维特征指导下的快速高分辨率测量。针对RST传感器获取的高分辨率三维信息是限制在与扫描平面垂直的方向上，提出了将三维轮廓投影到扫描平面上进行表面分块处理和特征提取的新方法；使用该方法进行了三维框架的分割；提出了二维边缘驱动的和三维分块表面驱动的两种测量路径规划的方法；最后将高分辨率距离数据与三维边缘融合，提高了RST传感器的测量效率，同时可以获得自然二次曲面的参数表达。
Information acquisition is an important branch of the information scienc. It's a result from the progress and intersection of traditional sensing technology and other information technologies, and is charactered by the high accuracy, high speed, integration and smartness in the process of information acquisition. 3-dimentional information acquisition is an active field in information acquisition, which studies methods of acquiring the geometrical structure and size of 3D objects. Normally it means getting the range data in addition to traditional 2D projective scale. With the development of then siecne and technology, the 3D imformation acqurisition is more and more important in research and industrial field.
In this thesis, based on a rotationally symmetric triangulation sensor with integrated vision system, some subjects in 3D information acquisition are investigated, including the sensor fusion, the validity, the uncertainty limit and the speed. Main works in this thesis include:
(1) The integration of rotationally symmetric triangulation (RST) sensor and the vision system is studied. The mockup of the sensor system is built and the fusion in sensors' physical layer is realized.
(2) The system error factors are investigated. The geometric optical model and the error model of RST sensor are studied. More attention is paid to errors caused by asymmetry which is resulted from eccentric laser illumination and tilted image sensor. It is pointed out that if some part of the ring image was lost, the uncertainty in measurement result will ascend in case of some what asymmetry. A compensation method based on neural network is presented. Then the basic performance parameters of the mockup are given.
(3) A detailed analysis of uncertainty limit in RST is presented. Speckle is also the fundamental uncertainty factor in this kind of sensors. The analytic expression of centroid uncertainty limit is derived from the statistic of laser speckle, and it is shown that the uncertainty limit in RST, and also in anamorphic triangulation, is dependent on the solid angle subtended by entrance pupil as seen from the illuminated laser spot, the triangulation angle, as well as the laser wavelength. The influence of aberration of optical system and surface roughness are also discussed.
(4) A method of getting the 3D edge characters based on the integrated vision system is studied. When using RST to acquire 3D information, a 2- dimensional scan is always needed. A novel symmetric multi-baseline matching based on the scanning movement is used to reduce matching error, and a subpixel matching based on quadratic interpolating is used to get a more smooth 3D edge. The matching is only done on character edges in images, so it is much more fast and robust.
(5) A method of fast measurement path planning of RST guided by the 3D edge characters is studied. Because the RST sensor always measures in the direction vertical to the scanning plane, the 3D edge characters acquired by vision system can be projected to the scan plane and make a path planning of the RST sensor. Two planning methods are presented, one is driven by the 2-dimesional edges, and the other is driven by 3-dimentional surface patches rounded by edges. Through path planning, measurement points are much less than before, and natural quadratic surface patches can be analytically expressed.
本文以三维信息获取技术为主线，针对集成视觉系统的旋转对称三角位移传感器(RST Rotationaly Symmetric Triangulation)，从信息获取的传感器融合、有效性、物理极限和测量效率等角度，研究了高分辨率三维信息获取技术。主要工作包括：
1研究了旋转对称型激光三角位移传感器(RST)与视觉测量系统的集成。给出了传感器的原理与设计，实现了多传感器在物理层上的融合。
2研究了RST传感器在安装和调整时引入的系统误差与补偿技术。提出了该传感器的几何光学测量模型；重点研究了由于投射激光偏离旋转轴和图像传感器的倾斜等因素造成系统旋转对称性下降而引起的误差因素；针对旋转对称性下降情况下的圆环缺失，提出了基于神经网络的误差补偿方法。给出了该传感器实验样机位移测量的不确定度。
3研究了RST位移测量的不确定度极限。重点研究了RST中的激光散斑现象，从散斑统计学的角度，首次推导了激光散斑引起的旋转对称三角法位移测量不确定度的极限，结果表明在光学粗糙表面上，该极限由投射激光波长，光学系统入瞳对投射光斑所张的立体角，以及光学系统主光轴与旋转轴的夹角确定；这一结论同样适用于其他变形成像(anamorphic)的激光三角法。
4基于RST的工作方式，研究了利用集成视觉系统的扫描移动来获得被测物体的低分辨率三维信息的方法。针对近景摄影测量中被测物缺乏足够的纹理细节问题，提出了一种基于对称多基线图像序列的匹配方法；利用亚象素匹配提高其精度，并获得一个连续的三维边缘；仅针对物体的边缘特征进行匹配，从而提高了三维信息获取的速度和鲁棒性。
5研究了三维特征指导下的快速高分辨率测量。针对RST传感器获取的高分辨率三维信息是限制在与扫描平面垂直的方向上，提出了将三维轮廓投影到扫描平面上进行表面分块处理和特征提取的新方法；使用该方法进行了三维框架的分割；提出了二维边缘驱动的和三维分块表面驱动的两种测量路径规划的方法；最后将高分辨率距离数据与三维边缘融合，提高了RST传感器的测量效率，同时可以获得自然二次曲面的参数表达。
Information acquisition is an important branch of the information scienc. It's a result from the progress and intersection of traditional sensing technology and other information technologies, and is charactered by the high accuracy, high speed, integration and smartness in the process of information acquisition. 3-dimentional information acquisition is an active field in information acquisition, which studies methods of acquiring the geometrical structure and size of 3D objects. Normally it means getting the range data in addition to traditional 2D projective scale. With the development of then siecne and technology, the 3D imformation acqurisition is more and more important in research and industrial field.
In this thesis, based on a rotationally symmetric triangulation sensor with integrated vision system, some subjects in 3D information acquisition are investigated, including the sensor fusion, the validity, the uncertainty limit and the speed. Main works in this thesis include:
(1) The integration of rotationally symmetric triangulation (RST) sensor and the vision system is studied. The mockup of the sensor system is built and the fusion in sensors' physical layer is realized.
(2) The system error factors are investigated. The geometric optical model and the error model of RST sensor are studied. More attention is paid to errors caused by asymmetry which is resulted from eccentric laser illumination and tilted image sensor. It is pointed out that if some part of the ring image was lost, the uncertainty in measurement result will ascend in case of some what asymmetry. A compensation method based on neural network is presented. Then the basic performance parameters of the mockup are given.
(3) A detailed analysis of uncertainty limit in RST is presented. Speckle is also the fundamental uncertainty factor in this kind of sensors. The analytic expression of centroid uncertainty limit is derived from the statistic of laser speckle, and it is shown that the uncertainty limit in RST, and also in anamorphic triangulation, is dependent on the solid angle subtended by entrance pupil as seen from the illuminated laser spot, the triangulation angle, as well as the laser wavelength. The influence of aberration of optical system and surface roughness are also discussed.
(4) A method of getting the 3D edge characters based on the integrated vision system is studied. When using RST to acquire 3D information, a 2- dimensional scan is always needed. A novel symmetric multi-baseline matching based on the scanning movement is used to reduce matching error, and a subpixel matching based on quadratic interpolating is used to get a more smooth 3D edge. The matching is only done on character edges in images, so it is much more fast and robust.
(5) A method of fast measurement path planning of RST guided by the 3D edge characters is studied. Because the RST sensor always measures in the direction vertical to the scanning plane, the 3D edge characters acquired by vision system can be projected to the scan plane and make a path planning of the RST sensor. Two planning methods are presented, one is driven by the 2-dimesional edges, and the other is driven by 3-dimentional surface patches rounded by edges. Through path planning, measurement points are much less than before, and natural quadratic surface patches can be analytically expressed.
引文
[1] TAO MEI, XIAOHUA WANG, JINGJING ZHANG. The Process and Model of Information Acquisition. International Journal of information Acquistion, 2004, 1 (2): 101-108
[2] David A．Forsyth，Jean Ponce著，林学訚，王宏译．计算机视觉．北京：电子工业出版社，2004
[3] Ott, P. Optical design of rotational symmetric triangulation sensors with low cost detectors based on reflective optics. SP1E 5144, Optical Measurement Systems for Industrial Inspection Ⅲ, Munich, Germany, 2003.
[4] Eckstein J., Ott P. Proof of Principle and Specification of a Rotational Symmetric Triangulation Sensor with Low Cost Reflection Optics. Photonics in Measurements, 2004, Frankfurt, Germany
[5] Eckstein, J., Ott, P. New type of rotationally symmetric triangulation sensors for optical distance measurement applications. REM - 6th International Workshop on Research and Education in Mechatronics, Annecy, France, 2005.
[6] Ott, P., Gao J., Eekstein J., Wang X. A rotationally symmetric triangulation sensor with low cost reflective optics. IEEE International Conference on Information Acquisition, Macau, China, 2005.
[7] Ott P., Eckstein J., Gao J. Design approach for systems with toroidal optical elements featuring a generalized Seheimpflug condition. 20th Congress of the International Commision for Optics, Changchun, China, 2005.
[8] Eckstein J., Lei W., Becker R.J., Jun G., OR P. Rotationally symmetric triangulation sensor with integrated object imaging using only one 2D detector. SPIE Photonies Europe, Strasbourg, France, 3-7 April, 2006
[9] Eckstein J., Lei W., Becker R.J., Jun G., OR P. Distance measurement by rotationally symmetric triangulation with integrated object imaging using only one 2D detector. OPTO 2006, 7th International Conference on Optical Technologies, Optical Sensors and Measuring Techniques, Nürnberg, Germany, 30 May - 1 June, 2006
[10] Eckstein J., Gao J., Ott P., Wang L., Wang X. New compact rotationally symmetric triangulation sensor with low-cost plastic optics. European Symposium on Optics and Optoelectronics (EEC), SPIE Photonics Europe, Prag, Czech Republic, April 16-20, 2007
[11] J. C. Danty. Some statistic properties of random speckle patterns in coherent and partially coherent illumination. OPTICA ACTA, 1970, 17(10): 761-772
[12] G. Hausler, P, Ettl, M. Schenk et al. Limits of Optical Range Sensors and How to Exploit Them. In Trends in Optics and Photonics, ICO Ⅳ, Springer Series in Optical Sciences, Vol 74: 328- 342
[13] Rainer G. Dorsch, Gerd Hausler, Jurgen M. Herrmann. Laser triangulation: fundamental uncertainty in distance measurement. Applied Optics, 1994, 33(7): 1306-1314
[14] Bejean Baribeau, Marc Rioux. Centroid fluctuations of speckled targets. Applied Optics, 1991, 30(26): 3752-3755
[15] Homberg D., ReiffE. -C., und Bauer K. Optische Distanzmessung mit hoher Auflosung Bis in den Nanometer- Bereich. elektro Automation, 48: 46-8, 1995
[16] WANG Lei, BO Mei, GAO Jun, OU ChunSheng. A Novel Double Triangulation 3D Camera Design. Proceedings of the 2006 IEEE International Conference on Information Acquisition, pp: 877-882, 2006
[17] GAO Jun, WANG Lei, YANG Xuezhi. A Survey of Desert Ant Navigation. IEEE Proceedings of 2005 International Conference on Information Acquisition, 99-104, 2005
[18] JUN GAO, LEI WANG, MEI BO, ZHIGUO FAN. INFORMATION ACQUISITION IN DESERT ANT NAVIGATION. International Journal of Information Acquisition 2006, 3(I): 1-11
[19] WANG Xiao Jia, GAO Jun, WANG Lei. A Survey of Subpixel Object Localization for Image Measurement, IEEE Proceedings of 2004 International Conference on Information Acquisition, 398-401, 2004
[20] 吴世雄．逆向工程中多传感器集成的智能化测量研究．浙江大学博士论文 2005
[21] 王磊，伯梅．高隽，偶春生，黄元庆．基于智能相机的高速三维表面信息获取．激光技术．2006，30(6)：657-660
[22] 伯梅，高隽，王磊，偶春生．用于三维重构的激光三角测量的标定方法．第十三届全国图象图形学学术会议．南京，中国．11.6-11.8，2006：11-15
[23] Tzung-Sz Shen, Jianbing Huang, Chia-Hsiang Menq. Multiple-Sensor Integration for Rapid and High-precision Coordinate Metrology IEEE/ASME Transactions on Mechatronics, 2000, 5(2): 110-121
[24] V. H. Chan. A Multi-Sensor Approach for Rapid Digitization and Data Segmentation in Reverse Engineering. Journal of Manufacturing Science and Engineering, 2000, 122(November): 725-733
[25] 胡寅．三维扫描仪与逆向工程关键技术研究．华中科技大学博士论文，2005
[26] David Gareia, Jose M. Sebastian y Zuniga, Francisco M. Sanchez Moreno. 3D inspection system for manufactured machine parts. Proceedings of SPIE Volume 3652 Machine Vision Applications in Industrial Inspection Ⅶ San Jose, CA; 1999; p. 250-260;
[27] 周莉萍，赵斌，李柱．无衍射光束在激光三角测量系统中的应用研究．激光技术，1998，22(1)：22-25
[28] J Davis, X Chen. A Laser Range Scanner Designed for Minimum Calibration Complexity. Third International Conference on 3-D Digital Imaging and Modeling (3DIM '01), 2001, 91-98
[29] 陈明君，赵清亮，姜承宾，李旦．双路激光-CCD零件尺寸动态检测仪的研制．压电与声光，2004，26(3)：182-185
[30] 李晶，吴章江，基于图像处理的激光双三角法测量三维曲面．激光与红外，2001，31(2)：87-89
[31] D. S. Pierce, T. S. Ng, B. R. Morrison. A novel laser triangulation technique for high precision distance measurement. Industry Applications Society Annual Meeting, 1992, 2: 1762-1769
[32] R. B. Fisher, D. K. Naidu. A Comparison of Algorithms for Subpixel Peak Detection. Advances in Image Processing, Multimedia and Machine Vision, Springer-Verlag, Heidelberg, 1996
[33] Stanke G. Zedler L. Zorn A. Weekend F. Weide H. G. Sub-pixel accuracy by optical measurement of large automobile components. Industrial Electronics Society, 1998. IECON '98. Proceedings of the 24th Annual Conference of the IEEE, Volume: 4, 2431-2433
[34] 孔兵，王昭，谭玉山，基于圆拟合的激光光斑中心检测算法．红外与激光工程，2002，31(3)：275-279
[35] 杨宪铭，贺俊吉，张广军，周富强．圆结构光光条中心亚像素级提取方法．光电工程，2004，31(4)：46-49
[36] 潘伟，赵毅，阮雪榆．结构光测量中获取高精度相位的新方法．光学学报，2004，24(5)：687-691)
[37] Gabor Felso, Laszlo Vajta. A NEW APPROACH TO THE CALIBRATION PROBLEMS OF 3D LASER SCANNER. PERIODICA POLYTECHNICA SER. EL. ENG, 2000, VOL. 44, NO. 3-4, PP. 271-282
[38] Tzung-sz Shen, Chia-Hsiang Menq. Automatic camera calibration for a multiple-sensor integrated coordinate measurement system. IEEE Transactions on robotics and automation, 2001, 17 (4): 502-507
[39] A. M. Bronstein, M. M. Bronstein, E. Gordon, R. Kimmel. High-Resolution Structured Light Range Scanner with Automatic Calibration. Technical Report C1S-2003-06 http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2003/CIS/CIS-2003-06.pdf
[40] Jokinen, O. Self-calibration of a light striping system by matching multiple 3-D profile maps. Proceedings of Second international Conference on 3-D Digital Imaging and Modeling, 4-8 Oct. 1999, Page(s): 180-190
[41] 王少清，庄葆华，张吉华，张文伟．激光三角位移计线性标定的研究。应用激光，1995，15(3)：117-121
[42] 邓春梅，陈吉红，周会成，师汉民．激光线结构光数控测量系统的标定．华中理工大学学 报，2000，28(3)：19-21
[43] Godin, R ioux, Beraldin, Levoy, Coumoyer, Blais. An Assessment of Laser Range Measurement on Marble Surfaces. 5th Conference on Optical 3D Measurement Techniques,Vienna, Austria., October 1-4, 2001, 49-56
[44] 邱景荣．随机误差和系统误差新定义诠释．中国计量，2001，62(1)：50-51A．
[45] 于金华，孙志超，潘东升．物理实验测量误差的合成．沈阳大学学报，1999，(2)：91-94
[46] 李慎安．有关测量误差的几个基本术语的新定义与有关问题．计量技术，1998，(4)：40-42
[47] Fang-Jung Shiou, Jung-Shiang Gao. Effect of slice thickness on the profile accuracy of model maker rapid prototyping measured by a circular triangulation laser probe. Intentional Journal of Advanced Manufacturing Technology, 2003, (22): 796-804
[48] F. Blais, J. -A. Beraldin, S. F. El-Hakim, Range Error Analysis of an Integrated Time-of-Flight, Triangulation, and Photogrammetric 3D Laser. SPlE Proceedings, AeroSense, Orlando, US, April 24-48, 2000, vol.4035
[49] 周利民，胡德洲，卢秉恒．激光扫描三角法测量精度因素的分析与研究．计量学报，1998，19(2)：
[50] 杨耀权，施仁，于希宁，高镗年．激光扫描三角法大型曲面测量中影响参数分析．西安交通大学学报，1999，33(7)：15-19
[51] 庄葆华，王少清，蒋诚志，张吉华，张文伟．激光三角位移汁接收光功率与被测表面倾斜的关系及倾斜角测量．中国激光，1995，22(8)：595-600
[52] 黄战华，蔡怀宇，李贺桥，张以谟．三角法激光测量系统的误差分析及消除方法．光电工程，2002，29(3)：58-61
[53] 洪昕，蒋诚志，陈林才，郑文学．激光三角法用于曲面测量中的影响参数分析．中国激光．1997，24(11)：993-996
[54] 徐玉春，阶则晓，冯国馨，王春海，张国雄．被测表面特征对激光测头特性的影响．天津大学学报，2001，34(6)：796-799
[55] Kyung-Chan Kim, Se-Baek Oh, Jong-Ahn Kim, Soohyun Kim, Yoon keun kwak. Compensation of Surface Inclination for Detecting in Optical Triangulation Sensors. Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference, 2000. IMTC 2000. Vol 3: 1292-1296
[56] F. Xi, Y. Liu, H. Y. Feng. Error Compensation for Three-Dimensional Line Laser Scanning Data. The International Journal of Advanced Manufacturing, 2001, 18: 211-216
[57] B. Curless. Better optical triangulation and volumetric reconstruction of complex models from range images. PhD thesis, Stanford University, 1996
[58] 王少清，庄葆华．激光三角法位移测量中被测物面倾斜产生测量误差的机理及其校正．应用光学，1995，16(2)：58-64
[59] 解则晓，张宏君，张国雄．影响激光三角测头测量精度的因素及其补偿措施．现代计量 测试，1999，(1)：23-26
[60] G. Hausler, S. Kreipl, R. Lampalzer, A. Schielzeth, B, Speilenberg. New Range Sensors at the Physical Limit of Measuring Uncertainty. Proceedings of the EOS Topical Meeting on Optoelectronics Distance Measurements and Applications, Nantes, July 8-10, 1997
[61] G. Hausler. About the Scaling Behaviour of Optical Range Sensors. Proceedings of the Third International Workshop on Automatic Processing of Fringe Patterns (Bremen), 1997
[62] 刘云峰．基于截面特征的反求工程CAD建模关键技术研究．浙江大学博士学位论文，2004
[63] 单东日．反求工程CAD建模中点云数据区域分割及特征约束重构技术研究．浙江大学博士学位论文，2003
[64] 武剑洁．基于点的散乱点云处理技术的研究．华中科技大学博士学位论文，2004
[65] 刘胜兰．逆向工程中自山曲面与规则曲面重建关键技术研究．南京航空航天大学博士学位论文，2004
[66] T Kasvand. Extraction edges in 3D range images to subpixel accuracy. 9th International Conference on Pattern Recognition, 1988, Nov. 14-17 vol. 1: 93-98
[67] M. Pauly, R. Keiser, M. Gross. Multi-Scale Feature Extraction on Point-Sampled Models. Proceedings of Annual Conference of the European Association for Computer Graphics, Granada, Spain, 2003, 32-41
[68] M. Pauly, M. Gross. Spectral Processing of Point-Sampled Geometry. ACM Proceedings on Computer Graphics, 2001. 35(4): 379-386
[69] Pauly M., Kobbelt L., Gross M. Multiresolution modeling of point-sampled geometry. CS Technical Report #378, September 16, 2002
[70] V. Carbone, M. Carocci, E. Savio, G. Sansoni, L. De Chiffre. Combination of a Vision System and a Coordinate Measuring Machine for the Reverse Engineering of Freeform Surfaces. International Journal of Advanced Manufacturing Technology, 2001, 17: 263-271
[71] K. H. Lee, H. Park. Automated Inspection Planning of Free-form Shape Parts by Laser Scanning. Robotics and Computer Integrated Manufacturing, 2000, 16(4): 901-210
[72] A. Heikki. CAD model-based planning and vision guidance for optical 3D co-ordinate measurement. PhD Thesis, University of Oulu, Finland, 1997
[73] K. H. Lee, S. Son, H. Park. CAD-based Laser Scan Planning System for Complex Surfaces. Euro-RP 2001, Paris, France, June 7-8, 2001, (http://kyebek9.gist.ac.kr/bk21/papers/conference_proceeding_international/CADbased%20laser%20scan%20planning%20systcm%20for%20complex%20surfaces_%E2%80%A6.pdf)
[74] I. Ainsworth, M. Ristic, D. Brujic. CAD-based measurement path planning for free-form shapes using contact probes. International Journal of Advanced Manufacturing Technology, 2000, 16: 23-31
[75] Z. Lin, J. Chow. Near Optimal Measuring Sequence Planning and Collision-Free Path Planning with a Dynamic Programming Method. International Journal of Advanced Manufacturing Technology, 2001, 18: 29-43
[76] Seokbae Son, Seungman Kim, Kwan H. Lee. Path planning of multi-patched freeform surfaces for laser scanning. International Journal of Advanced Manufacturing Technology, 2001, 18: 29-43
[77] Wang Xiangjun. Wang Yizhong, Ye Shenghua. Methods of Visual Recognition, Positioning and Orientating of 3-D Simple Geometric Workpiece. Transactions of Tianjin University, 1998, 4(2): 144-148
[78] L. C. Chen, G. C. Lin. A Vision-aided reverse engineering approach to reconstructing free-form surfaces. Robotics & Computer-lntegrated Manufacturing, 1997, 13(4): 323-336
[79] B. Weiss. New In-Line Laser Technology in Automotive Parts Measurements. http://mecadserv1.technion.ac.il/public_html/IK05/weiss.pdf
[80] Shree K. Nayar, Katsushi lkeuchi, Takeo Kanade. Surface Reflection: Physical and Geometrical Perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1991, Vol.13 NO. 7: 611-634
[81] 飞思科技产品研发中心．神经网络理论与Matlab7实现．北京，电子工业出版社，2005
[82] 高隽．人工神经网络原理及仿真实例．北京，机械工业出版社，2003，PP：44-63
[83] Briers J. D. Surface roughness evaluation. Speckle Metrology. New York: Marcel Dekker, 1993, pp: 373-426
[84] 戚康男．秦克诚．程路．统计光学导论．天津，天津南开大学出版社 1987，PP：562-575
[85] Roger Y. Tsai. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf cameras and TV lenses. IEEE Journal of Robotics and Automation, 1987, RA-3(4): 323-344
[86] Jean-Yves Bouguet. Camera Calibration Toolbox for Matlab. http://www.vision.ealtech.edu/bouguetj/calib_doc/index.htmi#parameters
[87] 杨敏．多视几何和基于未标定图像的三维重构．南京航空航天大学博士学位论文．2003
[88] 王宇宙．计算机视觉三维重建理论与应用．西北大学博士学位论文．2004
[89] 张可．基于双目立体视觉原理的自由曲面三维重构．华中科技大学博士学位论文 2005
[90] T. Melen. Geometrical modelling and calibration of video cameras for underwater navigation. PhD thesis,. Institutt for teknisk kybernetikk, Norges tekniske hogskole, 1994
[91] Ameri Society Photogrammetry, Manual of Photogrammetry. 4th ed. American Society of Photogrammetry, Falls Church, Virginia, USA, 1980
[92] H. A. Martins, J. R. Birk, R. 8. Kelley. Camera Models Based on Data from Two Calibration Plane. Computer Graphics Image Processing, 1981, 17(2): 173-180
[93] GuoQing Wei, SongDe Ma. Two plane camera calibration: a unified model. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Proceedings CVPR'91,, 3-6 Jun 1991, pp: 133-138
[94] Heikkil J, Silven O. A four-step camera calibration procedure with implicit image correction. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), San Juan, Puerto Rico, 1997, pp: 1106～1112
[95] Zhang Z. Y. Flexible camera calibration by viewing a plane from unknown orientations. Proceedings of the International Conference on Computer Vision (ICCV'99) 1999, pp: 666～673
[96] Sturm P. Maybank S. On plane-based camera calibration: A general algorithm, singularities, applications. IEEE Proceedings of the Conference on Computer Vision and Pattern Recognition, Fort Collins, Colorado, USA, 1999, pp: 432-437
[97] 王年．三维重构中关键算法研究．安徽大学博士学位论文，2005
[98] ZHANG Zhengyou, DERICHE R., FAUGERAS O., et al. A robust technique for matching two unealibrated images through the recovery of the unknown epipolar geometry. Artificial Intelligence, 1995, 78: 87-119
[99] E. Z. Psarakis, G. D. Evangelidis. An enhanced correlation-based method for stereo correspondence with sub-pixel accuracy. Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV05), 2005, pp: 907-912
[100] P. Werth, S. Seherer. Robust Subpixel Stereo Matching by Relaxation of Match Candidates. Proceedings of First International Workshop on Image and Signal Processing and Analysis, 2000, pp: 189-194
[101] R. Szeliski. D. Sharstein. Symmetric Sub-Pixel Stereo. Matching. Proceedings of Seventh European Conference on Computer Vision, 2002, 2: 525-540
[102] Peter Kovesi. Matlab and Octave Functions for Computer Vision and Image Processing. http:/www.csse.uwa.edu.au/～pk/research/matlabfns/
[103] 孙向军．场景三维重建的若干关键技术研究．南京理工大学博士学位论文，2004
[104] 刘正东．计算机视觉中立体匹配技术的研究．南京理工大学博士学位论文，2005
[105] C. Schmid, R. Mohr. Local gray value invariants for image retrieval. IEEE Trans on Pattanal and Math Intell, 1997, 19(5): 530-535
[106] V. Gouet, P. Montesinos, and D. Pel. A fast matching method for color unealibrated images using differential invariants. British Machine Vision. Conference, volume 1, pp: 367-376
[107] P. Montesinos, V. Gouet, R. Deriche. Differential lnvariants for Color Images. Proceedings of 14th. International. Conference on Pattern Recognition, Brisbane, Australia, 1998, pp: 838-840
[108] David G Lowe. Object Recognition from Local Scale-lnvariant Features. International Conference on Computer Vision, Greece, 1999: 1150-1157
[109] A. Baumberg. Reliable feature matching across widely separated views. Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR00), 2000, pp: 774-781
[110] 孙向军，曹立鑫，刘风山．基于角仿射不变的特征匹配．中国图象图形学报，2004，9(5)：589-593
[111] 王跃宗．SLM显微立体视觉量化和三维数据重构研究．大连理工大学博士学位论文，2003
[112] T. Tuytelaars, L. Van Gool. Wide baseline stereo matching based on local affinely invariant. Regions. Proceedings British Machine Vision Conference, Sept. 2000, pp: 412-422
[113] M. Okutomi, T. Kanade. A multiple-baseline stereo. IEEE Transactions of Pattern Analysis and Machine Intelligence, April 1993, 15(4): 353-363
[114] M. Shirnizu, M. Okutomi. Precise subpixel estimation on area-based matching. Systems. and Computers in Japan, July 2002, 33(7): 1-10
[115] Z. D. Lan, R. Mohr. Direct linear sub-pixel correlation by incorporation of neighbor pixels information and robust estimation of window transformation.. Machine Vision and Applications, Springer-Verlag, 1998, 10: 256-268
[116] 吕震．浙江大学博士学位论文，2002
[117] S. F. El-Hakim, J. -A. Beraldin. On the Integration of Range and Intensity Data to Improve Vision-based Three-dimensional Measurements. Videometrics Ⅲ, Proc. SPIE. 2350, 1994, pp: 306-321
[118] J. A. Beraldin. Integration of Laser Scanning and Close-range Photogrammetry - the Last Decade and. Beyond. Proceedings of the ⅩⅩth ISPRS congress, Commission Ⅶ, Istanbul, Turkey, July 12-23 2004, NRC 46567, pp: 972-983
[119] Baltsavias. E. P. A comparison between photogrammetry and laser scanning. ISPRS Journal of Photogrammetry & Remote Sensing, 54, pp: 83-94
[120] Bather D., Mills J., Bryan P. G Laser Scanning and Photogrammetry-21th Century Metrology. CIPA 2001 Intern. Symp., Sruveying and Documentation of Historic Buildings, Monuments, Sites, Potsdam, Germany
[121] El-Hakim. S. F., Beraldin J. A., Biais E A Comparative Evaluation of Passive and Active 3-D Vision Systems. Digital Photogrammetry and Remote Sensing '95, St-Petersburg, June 25-30, SPIE Vol.2646, pp: 14-25
[122] Velios A., Harrison J. P. Laser scanning and digital close range photogrammetry for capturing 3D archaeological objects: a comparison of quality and practicality. Archaeological Informatics: Pushing the Envelope, CAA2001, Oxford, pp: 205-211
[123] Lawrence A．Klein著，戴业平等译．多传感器数据融合理论及应用．北京，北京理工大学出版社，2004
[124] Hall D. L., Llinas J. An Introduction to Multisensor Data Fusion. Proceedings of the IEEE, 85(1): 6-23
[125] Llinas J., Waltz E. Multisensor Data Fusion. Boston, MA, Artech House, 1990
[126] Johnson A. E., Kang S. B. Registration and integration of textured 3D data. First International Conference on Recent Advances in 3D digital Imaging and Modeling, Ottawa, May 12-15, pp: 234-241
[127] Johnson A. E., Manduchi R. Probabilistic 3D Fusion for Adaptive Resolution Surface Generation. 1EEE Proceeding of the International Symposium on 3D Data Processing Visualization and Transmission, Padova, Italy, June 19-21, 2002, pp: 578-587
[128] Blais F. A Review of 20 Years of Range Sensor Development. Journal of Electronic Imaging, 2004, 13(1): 231-243
[129] http://www.mm.hs-heiibronn.de/ott/
[2] David A．Forsyth，Jean Ponce著，林学訚，王宏译．计算机视觉．北京：电子工业出版社，2004
[3] Ott, P. Optical design of rotational symmetric triangulation sensors with low cost detectors based on reflective optics. SP1E 5144, Optical Measurement Systems for Industrial Inspection Ⅲ, Munich, Germany, 2003.
[4] Eckstein J., Ott P. Proof of Principle and Specification of a Rotational Symmetric Triangulation Sensor with Low Cost Reflection Optics. Photonics in Measurements, 2004, Frankfurt, Germany
[5] Eckstein, J., Ott, P. New type of rotationally symmetric triangulation sensors for optical distance measurement applications. REM - 6th International Workshop on Research and Education in Mechatronics, Annecy, France, 2005.
[6] Ott, P., Gao J., Eekstein J., Wang X. A rotationally symmetric triangulation sensor with low cost reflective optics. IEEE International Conference on Information Acquisition, Macau, China, 2005.
[7] Ott P., Eckstein J., Gao J. Design approach for systems with toroidal optical elements featuring a generalized Seheimpflug condition. 20th Congress of the International Commision for Optics, Changchun, China, 2005.
[8] Eckstein J., Lei W., Becker R.J., Jun G., OR P. Rotationally symmetric triangulation sensor with integrated object imaging using only one 2D detector. SPIE Photonies Europe, Strasbourg, France, 3-7 April, 2006
[9] Eckstein J., Lei W., Becker R.J., Jun G., OR P. Distance measurement by rotationally symmetric triangulation with integrated object imaging using only one 2D detector. OPTO 2006, 7th International Conference on Optical Technologies, Optical Sensors and Measuring Techniques, Nürnberg, Germany, 30 May - 1 June, 2006
[10] Eckstein J., Gao J., Ott P., Wang L., Wang X. New compact rotationally symmetric triangulation sensor with low-cost plastic optics. European Symposium on Optics and Optoelectronics (EEC), SPIE Photonics Europe, Prag, Czech Republic, April 16-20, 2007
[11] J. C. Danty. Some statistic properties of random speckle patterns in coherent and partially coherent illumination. OPTICA ACTA, 1970, 17(10): 761-772
[12] G. Hausler, P, Ettl, M. Schenk et al. Limits of Optical Range Sensors and How to Exploit Them. In Trends in Optics and Photonics, ICO Ⅳ, Springer Series in Optical Sciences, Vol 74: 328- 342
[13] Rainer G. Dorsch, Gerd Hausler, Jurgen M. Herrmann. Laser triangulation: fundamental uncertainty in distance measurement. Applied Optics, 1994, 33(7): 1306-1314
[14] Bejean Baribeau, Marc Rioux. Centroid fluctuations of speckled targets. Applied Optics, 1991, 30(26): 3752-3755
[15] Homberg D., ReiffE. -C., und Bauer K. Optische Distanzmessung mit hoher Auflosung Bis in den Nanometer- Bereich. elektro Automation, 48: 46-8, 1995
[16] WANG Lei, BO Mei, GAO Jun, OU ChunSheng. A Novel Double Triangulation 3D Camera Design. Proceedings of the 2006 IEEE International Conference on Information Acquisition, pp: 877-882, 2006
[17] GAO Jun, WANG Lei, YANG Xuezhi. A Survey of Desert Ant Navigation. IEEE Proceedings of 2005 International Conference on Information Acquisition, 99-104, 2005
[18] JUN GAO, LEI WANG, MEI BO, ZHIGUO FAN. INFORMATION ACQUISITION IN DESERT ANT NAVIGATION. International Journal of Information Acquisition 2006, 3(I): 1-11
[19] WANG Xiao Jia, GAO Jun, WANG Lei. A Survey of Subpixel Object Localization for Image Measurement, IEEE Proceedings of 2004 International Conference on Information Acquisition, 398-401, 2004
[20] 吴世雄．逆向工程中多传感器集成的智能化测量研究．浙江大学博士论文 2005
[21] 王磊，伯梅．高隽，偶春生，黄元庆．基于智能相机的高速三维表面信息获取．激光技术．2006，30(6)：657-660
[22] 伯梅，高隽，王磊，偶春生．用于三维重构的激光三角测量的标定方法．第十三届全国图象图形学学术会议．南京，中国．11.6-11.8，2006：11-15
[23] Tzung-Sz Shen, Jianbing Huang, Chia-Hsiang Menq. Multiple-Sensor Integration for Rapid and High-precision Coordinate Metrology IEEE/ASME Transactions on Mechatronics, 2000, 5(2): 110-121
[24] V. H. Chan. A Multi-Sensor Approach for Rapid Digitization and Data Segmentation in Reverse Engineering. Journal of Manufacturing Science and Engineering, 2000, 122(November): 725-733
[25] 胡寅．三维扫描仪与逆向工程关键技术研究．华中科技大学博士论文，2005
[26] David Gareia, Jose M. Sebastian y Zuniga, Francisco M. Sanchez Moreno. 3D inspection system for manufactured machine parts. Proceedings of SPIE Volume 3652 Machine Vision Applications in Industrial Inspection Ⅶ San Jose, CA; 1999; p. 250-260;
[27] 周莉萍，赵斌，李柱．无衍射光束在激光三角测量系统中的应用研究．激光技术，1998，22(1)：22-25
[28] J Davis, X Chen. A Laser Range Scanner Designed for Minimum Calibration Complexity. Third International Conference on 3-D Digital Imaging and Modeling (3DIM '01), 2001, 91-98
[29] 陈明君，赵清亮，姜承宾，李旦．双路激光-CCD零件尺寸动态检测仪的研制．压电与声光，2004，26(3)：182-185
[30] 李晶，吴章江，基于图像处理的激光双三角法测量三维曲面．激光与红外，2001，31(2)：87-89
[31] D. S. Pierce, T. S. Ng, B. R. Morrison. A novel laser triangulation technique for high precision distance measurement. Industry Applications Society Annual Meeting, 1992, 2: 1762-1769
[32] R. B. Fisher, D. K. Naidu. A Comparison of Algorithms for Subpixel Peak Detection. Advances in Image Processing, Multimedia and Machine Vision, Springer-Verlag, Heidelberg, 1996
[33] Stanke G. Zedler L. Zorn A. Weekend F. Weide H. G. Sub-pixel accuracy by optical measurement of large automobile components. Industrial Electronics Society, 1998. IECON '98. Proceedings of the 24th Annual Conference of the IEEE, Volume: 4, 2431-2433
[34] 孔兵，王昭，谭玉山，基于圆拟合的激光光斑中心检测算法．红外与激光工程，2002，31(3)：275-279
[35] 杨宪铭，贺俊吉，张广军，周富强．圆结构光光条中心亚像素级提取方法．光电工程，2004，31(4)：46-49
[36] 潘伟，赵毅，阮雪榆．结构光测量中获取高精度相位的新方法．光学学报，2004，24(5)：687-691)
[37] Gabor Felso, Laszlo Vajta. A NEW APPROACH TO THE CALIBRATION PROBLEMS OF 3D LASER SCANNER. PERIODICA POLYTECHNICA SER. EL. ENG, 2000, VOL. 44, NO. 3-4, PP. 271-282
[38] Tzung-sz Shen, Chia-Hsiang Menq. Automatic camera calibration for a multiple-sensor integrated coordinate measurement system. IEEE Transactions on robotics and automation, 2001, 17 (4): 502-507
[39] A. M. Bronstein, M. M. Bronstein, E. Gordon, R. Kimmel. High-Resolution Structured Light Range Scanner with Automatic Calibration. Technical Report C1S-2003-06 http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2003/CIS/CIS-2003-06.pdf
[40] Jokinen, O. Self-calibration of a light striping system by matching multiple 3-D profile maps. Proceedings of Second international Conference on 3-D Digital Imaging and Modeling, 4-8 Oct. 1999, Page(s): 180-190
[41] 王少清，庄葆华，张吉华，张文伟．激光三角位移计线性标定的研究。应用激光，1995，15(3)：117-121
[42] 邓春梅，陈吉红，周会成，师汉民．激光线结构光数控测量系统的标定．华中理工大学学 报，2000，28(3)：19-21
[43] Godin, R ioux, Beraldin, Levoy, Coumoyer, Blais. An Assessment of Laser Range Measurement on Marble Surfaces. 5th Conference on Optical 3D Measurement Techniques,Vienna, Austria., October 1-4, 2001, 49-56
[44] 邱景荣．随机误差和系统误差新定义诠释．中国计量，2001，62(1)：50-51A．
[45] 于金华，孙志超，潘东升．物理实验测量误差的合成．沈阳大学学报，1999，(2)：91-94
[46] 李慎安．有关测量误差的几个基本术语的新定义与有关问题．计量技术，1998，(4)：40-42
[47] Fang-Jung Shiou, Jung-Shiang Gao. Effect of slice thickness on the profile accuracy of model maker rapid prototyping measured by a circular triangulation laser probe. Intentional Journal of Advanced Manufacturing Technology, 2003, (22): 796-804
[48] F. Blais, J. -A. Beraldin, S. F. El-Hakim, Range Error Analysis of an Integrated Time-of-Flight, Triangulation, and Photogrammetric 3D Laser. SPlE Proceedings, AeroSense, Orlando, US, April 24-48, 2000, vol.4035
[49] 周利民，胡德洲，卢秉恒．激光扫描三角法测量精度因素的分析与研究．计量学报，1998，19(2)：
[50] 杨耀权，施仁，于希宁，高镗年．激光扫描三角法大型曲面测量中影响参数分析．西安交通大学学报，1999，33(7)：15-19
[51] 庄葆华，王少清，蒋诚志，张吉华，张文伟．激光三角位移汁接收光功率与被测表面倾斜的关系及倾斜角测量．中国激光，1995，22(8)：595-600
[52] 黄战华，蔡怀宇，李贺桥，张以谟．三角法激光测量系统的误差分析及消除方法．光电工程，2002，29(3)：58-61
[53] 洪昕，蒋诚志，陈林才，郑文学．激光三角法用于曲面测量中的影响参数分析．中国激光．1997，24(11)：993-996
[54] 徐玉春，阶则晓，冯国馨，王春海，张国雄．被测表面特征对激光测头特性的影响．天津大学学报，2001，34(6)：796-799
[55] Kyung-Chan Kim, Se-Baek Oh, Jong-Ahn Kim, Soohyun Kim, Yoon keun kwak. Compensation of Surface Inclination for Detecting in Optical Triangulation Sensors. Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference, 2000. IMTC 2000. Vol 3: 1292-1296
[56] F. Xi, Y. Liu, H. Y. Feng. Error Compensation for Three-Dimensional Line Laser Scanning Data. The International Journal of Advanced Manufacturing, 2001, 18: 211-216
[57] B. Curless. Better optical triangulation and volumetric reconstruction of complex models from range images. PhD thesis, Stanford University, 1996
[58] 王少清，庄葆华．激光三角法位移测量中被测物面倾斜产生测量误差的机理及其校正．应用光学，1995，16(2)：58-64
[59] 解则晓，张宏君，张国雄．影响激光三角测头测量精度的因素及其补偿措施．现代计量 测试，1999，(1)：23-26
[60] G. Hausler, S. Kreipl, R. Lampalzer, A. Schielzeth, B, Speilenberg. New Range Sensors at the Physical Limit of Measuring Uncertainty. Proceedings of the EOS Topical Meeting on Optoelectronics Distance Measurements and Applications, Nantes, July 8-10, 1997
[61] G. Hausler. About the Scaling Behaviour of Optical Range Sensors. Proceedings of the Third International Workshop on Automatic Processing of Fringe Patterns (Bremen), 1997
[62] 刘云峰．基于截面特征的反求工程CAD建模关键技术研究．浙江大学博士学位论文，2004
[63] 单东日．反求工程CAD建模中点云数据区域分割及特征约束重构技术研究．浙江大学博士学位论文，2003
[64] 武剑洁．基于点的散乱点云处理技术的研究．华中科技大学博士学位论文，2004
[65] 刘胜兰．逆向工程中自山曲面与规则曲面重建关键技术研究．南京航空航天大学博士学位论文，2004
[66] T Kasvand. Extraction edges in 3D range images to subpixel accuracy. 9th International Conference on Pattern Recognition, 1988, Nov. 14-17 vol. 1: 93-98
[67] M. Pauly, R. Keiser, M. Gross. Multi-Scale Feature Extraction on Point-Sampled Models. Proceedings of Annual Conference of the European Association for Computer Graphics, Granada, Spain, 2003, 32-41
[68] M. Pauly, M. Gross. Spectral Processing of Point-Sampled Geometry. ACM Proceedings on Computer Graphics, 2001. 35(4): 379-386
[69] Pauly M., Kobbelt L., Gross M. Multiresolution modeling of point-sampled geometry. CS Technical Report #378, September 16, 2002
[70] V. Carbone, M. Carocci, E. Savio, G. Sansoni, L. De Chiffre. Combination of a Vision System and a Coordinate Measuring Machine for the Reverse Engineering of Freeform Surfaces. International Journal of Advanced Manufacturing Technology, 2001, 17: 263-271
[71] K. H. Lee, H. Park. Automated Inspection Planning of Free-form Shape Parts by Laser Scanning. Robotics and Computer Integrated Manufacturing, 2000, 16(4): 901-210
[72] A. Heikki. CAD model-based planning and vision guidance for optical 3D co-ordinate measurement. PhD Thesis, University of Oulu, Finland, 1997
[73] K. H. Lee, S. Son, H. Park. CAD-based Laser Scan Planning System for Complex Surfaces. Euro-RP 2001, Paris, France, June 7-8, 2001, (http://kyebek9.gist.ac.kr/bk21/papers/conference_proceeding_international/CADbased%20laser%20scan%20planning%20systcm%20for%20complex%20surfaces_%E2%80%A6.pdf)
[74] I. Ainsworth, M. Ristic, D. Brujic. CAD-based measurement path planning for free-form shapes using contact probes. International Journal of Advanced Manufacturing Technology, 2000, 16: 23-31
[75] Z. Lin, J. Chow. Near Optimal Measuring Sequence Planning and Collision-Free Path Planning with a Dynamic Programming Method. International Journal of Advanced Manufacturing Technology, 2001, 18: 29-43
[76] Seokbae Son, Seungman Kim, Kwan H. Lee. Path planning of multi-patched freeform surfaces for laser scanning. International Journal of Advanced Manufacturing Technology, 2001, 18: 29-43
[77] Wang Xiangjun. Wang Yizhong, Ye Shenghua. Methods of Visual Recognition, Positioning and Orientating of 3-D Simple Geometric Workpiece. Transactions of Tianjin University, 1998, 4(2): 144-148
[78] L. C. Chen, G. C. Lin. A Vision-aided reverse engineering approach to reconstructing free-form surfaces. Robotics & Computer-lntegrated Manufacturing, 1997, 13(4): 323-336
[79] B. Weiss. New In-Line Laser Technology in Automotive Parts Measurements. http://mecadserv1.technion.ac.il/public_html/IK05/weiss.pdf
[80] Shree K. Nayar, Katsushi lkeuchi, Takeo Kanade. Surface Reflection: Physical and Geometrical Perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1991, Vol.13 NO. 7: 611-634
[81] 飞思科技产品研发中心．神经网络理论与Matlab7实现．北京，电子工业出版社，2005
[82] 高隽．人工神经网络原理及仿真实例．北京，机械工业出版社，2003，PP：44-63
[83] Briers J. D. Surface roughness evaluation. Speckle Metrology. New York: Marcel Dekker, 1993, pp: 373-426
[84] 戚康男．秦克诚．程路．统计光学导论．天津，天津南开大学出版社 1987，PP：562-575
[85] Roger Y. Tsai. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf cameras and TV lenses. IEEE Journal of Robotics and Automation, 1987, RA-3(4): 323-344
[86] Jean-Yves Bouguet. Camera Calibration Toolbox for Matlab. http://www.vision.ealtech.edu/bouguetj/calib_doc/index.htmi#parameters
[87] 杨敏．多视几何和基于未标定图像的三维重构．南京航空航天大学博士学位论文．2003
[88] 王宇宙．计算机视觉三维重建理论与应用．西北大学博士学位论文．2004
[89] 张可．基于双目立体视觉原理的自由曲面三维重构．华中科技大学博士学位论文 2005
[90] T. Melen. Geometrical modelling and calibration of video cameras for underwater navigation. PhD thesis,. Institutt for teknisk kybernetikk, Norges tekniske hogskole, 1994
[91] Ameri Society Photogrammetry, Manual of Photogrammetry. 4th ed. American Society of Photogrammetry, Falls Church, Virginia, USA, 1980
[92] H. A. Martins, J. R. Birk, R. 8. Kelley. Camera Models Based on Data from Two Calibration Plane. Computer Graphics Image Processing, 1981, 17(2): 173-180
[93] GuoQing Wei, SongDe Ma. Two plane camera calibration: a unified model. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Proceedings CVPR'91,, 3-6 Jun 1991, pp: 133-138
[94] Heikkil J, Silven O. A four-step camera calibration procedure with implicit image correction. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), San Juan, Puerto Rico, 1997, pp: 1106～1112
[95] Zhang Z. Y. Flexible camera calibration by viewing a plane from unknown orientations. Proceedings of the International Conference on Computer Vision (ICCV'99) 1999, pp: 666～673
[96] Sturm P. Maybank S. On plane-based camera calibration: A general algorithm, singularities, applications. IEEE Proceedings of the Conference on Computer Vision and Pattern Recognition, Fort Collins, Colorado, USA, 1999, pp: 432-437
[97] 王年．三维重构中关键算法研究．安徽大学博士学位论文，2005
[98] ZHANG Zhengyou, DERICHE R., FAUGERAS O., et al. A robust technique for matching two unealibrated images through the recovery of the unknown epipolar geometry. Artificial Intelligence, 1995, 78: 87-119
[99] E. Z. Psarakis, G. D. Evangelidis. An enhanced correlation-based method for stereo correspondence with sub-pixel accuracy. Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV05), 2005, pp: 907-912
[100] P. Werth, S. Seherer. Robust Subpixel Stereo Matching by Relaxation of Match Candidates. Proceedings of First International Workshop on Image and Signal Processing and Analysis, 2000, pp: 189-194
[101] R. Szeliski. D. Sharstein. Symmetric Sub-Pixel Stereo. Matching. Proceedings of Seventh European Conference on Computer Vision, 2002, 2: 525-540
[102] Peter Kovesi. Matlab and Octave Functions for Computer Vision and Image Processing. http:/www.csse.uwa.edu.au/～pk/research/matlabfns/
[103] 孙向军．场景三维重建的若干关键技术研究．南京理工大学博士学位论文，2004
[104] 刘正东．计算机视觉中立体匹配技术的研究．南京理工大学博士学位论文，2005
[105] C. Schmid, R. Mohr. Local gray value invariants for image retrieval. IEEE Trans on Pattanal and Math Intell, 1997, 19(5): 530-535
[106] V. Gouet, P. Montesinos, and D. Pel. A fast matching method for color unealibrated images using differential invariants. British Machine Vision. Conference, volume 1, pp: 367-376
[107] P. Montesinos, V. Gouet, R. Deriche. Differential lnvariants for Color Images. Proceedings of 14th. International. Conference on Pattern Recognition, Brisbane, Australia, 1998, pp: 838-840
[108] David G Lowe. Object Recognition from Local Scale-lnvariant Features. International Conference on Computer Vision, Greece, 1999: 1150-1157
[109] A. Baumberg. Reliable feature matching across widely separated views. Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR00), 2000, pp: 774-781
[110] 孙向军，曹立鑫，刘风山．基于角仿射不变的特征匹配．中国图象图形学报，2004，9(5)：589-593
[111] 王跃宗．SLM显微立体视觉量化和三维数据重构研究．大连理工大学博士学位论文，2003
[112] T. Tuytelaars, L. Van Gool. Wide baseline stereo matching based on local affinely invariant. Regions. Proceedings British Machine Vision Conference, Sept. 2000, pp: 412-422
[113] M. Okutomi, T. Kanade. A multiple-baseline stereo. IEEE Transactions of Pattern Analysis and Machine Intelligence, April 1993, 15(4): 353-363
[114] M. Shirnizu, M. Okutomi. Precise subpixel estimation on area-based matching. Systems. and Computers in Japan, July 2002, 33(7): 1-10
[115] Z. D. Lan, R. Mohr. Direct linear sub-pixel correlation by incorporation of neighbor pixels information and robust estimation of window transformation.. Machine Vision and Applications, Springer-Verlag, 1998, 10: 256-268
[116] 吕震．浙江大学博士学位论文，2002
[117] S. F. El-Hakim, J. -A. Beraldin. On the Integration of Range and Intensity Data to Improve Vision-based Three-dimensional Measurements. Videometrics Ⅲ, Proc. SPIE. 2350, 1994, pp: 306-321
[118] J. A. Beraldin. Integration of Laser Scanning and Close-range Photogrammetry - the Last Decade and. Beyond. Proceedings of the ⅩⅩth ISPRS congress, Commission Ⅶ, Istanbul, Turkey, July 12-23 2004, NRC 46567, pp: 972-983
[119] Baltsavias. E. P. A comparison between photogrammetry and laser scanning. ISPRS Journal of Photogrammetry & Remote Sensing, 54, pp: 83-94
[120] Bather D., Mills J., Bryan P. G Laser Scanning and Photogrammetry-21th Century Metrology. CIPA 2001 Intern. Symp., Sruveying and Documentation of Historic Buildings, Monuments, Sites, Potsdam, Germany
[121] El-Hakim. S. F., Beraldin J. A., Biais E A Comparative Evaluation of Passive and Active 3-D Vision Systems. Digital Photogrammetry and Remote Sensing '95, St-Petersburg, June 25-30, SPIE Vol.2646, pp: 14-25
[122] Velios A., Harrison J. P. Laser scanning and digital close range photogrammetry for capturing 3D archaeological objects: a comparison of quality and practicality. Archaeological Informatics: Pushing the Envelope, CAA2001, Oxford, pp: 205-211
[123] Lawrence A．Klein著，戴业平等译．多传感器数据融合理论及应用．北京，北京理工大学出版社，2004
[124] Hall D. L., Llinas J. An Introduction to Multisensor Data Fusion. Proceedings of the IEEE, 85(1): 6-23
[125] Llinas J., Waltz E. Multisensor Data Fusion. Boston, MA, Artech House, 1990
[126] Johnson A. E., Kang S. B. Registration and integration of textured 3D data. First International Conference on Recent Advances in 3D digital Imaging and Modeling, Ottawa, May 12-15, pp: 234-241
[127] Johnson A. E., Manduchi R. Probabilistic 3D Fusion for Adaptive Resolution Surface Generation. 1EEE Proceeding of the International Symposium on 3D Data Processing Visualization and Transmission, Padova, Italy, June 19-21, 2002, pp: 578-587
[128] Blais F. A Review of 20 Years of Range Sensor Development. Journal of Electronic Imaging, 2004, 13(1): 231-243
[129] http://www.mm.hs-heiibronn.de/ott/