Block Adjustment of Vehicle-borne Multi-camera Rig Images Using Extended Collinearity Equations

doi:10.11947/j.AGCS.2017.20160464

Abstract

Abstract: This paper introduces the extended collinearity equations into aerial triangulation of the vehicle-borne multi-camera rig images to improve the positioning accuracy. The cameras in a multi-camera rig are rigidly fixed and the relative position and orientation parameters among the mono cameras of multi-camera rig can be calibrated accurately, so the extended collinearity equations can be used to extend the imaging unit from a mono camera image to multiple images of multi-camera rigs. Compared with the existing spherical models, including the spherical ideal model and the spherical rigorous model, the extended collinearity equations used in this paper avoid the spherical projection error and fusion error caused by the misalignment of projection centers. Experimental results show that the method omits the processing procedure of model projection and fusion of overlap areas, which avoids the precision loss and complicated processing procedure, and finally obtains more robustness triangulation net, more precise and robust position accuracy.

Key words: vehicle-borne multi-camera rigs, extended collinear equations, relative position and orientation parameters, aerial triangulation

CLC Number:

P237

YIN Li, WANG Yidan. Block Adjustment of Vehicle-borne Multi-camera Rig Images Using Extended Collinearity Equations[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(4): 460-467.

References

[1] SUNG C K, LU C H. Single-camera Panoramic Stereo System Model Based on Skew Ray Tracing[J]. Optik-international Journal for Light and Electron Optics, 2012, 123(7): 594-603.
[2] LI Shigang. Monitoring Around a Vehicle by a Spherical Image Sensor[J]. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(4): 541-550.
[3] PARIAN J A, GRUEN A. Sensor Modeling, Self-calibration and Accuracy Testing of Panoramic Cameras and Laser Scanners[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2010, 65(1): 60-76.
[4] SATO T, IKEDA S, YOKOYA N. Extrinsic Camera Parameter Recovery from Multiple Image Sequences Captured by an Omni-directional Multi-camera System[M]//PAJDLA T, MATAS J. Computer Vision-ECCV 2004. Berlin: Springer, 2004: 326-340.
[5] GLEDHILL D, TIAN Guiyun, TAYLOR D, et al. Panoramic Imaging—A Review[J]. Computers & Graphics, 2003, 27(3): 435-445.
[6] MICUSIK B, KOSECKA J. Piecewise Planar City 3D Modeling from Street View Panoramic Sequences[C]//Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami: IEEE, 2009: 2906-2912.
[7] 张正鹏, 江万寿, 张靖. 光流特征聚类的车载全景序列影像匹配方法[J]. 测绘学报, 2014, 43(12): 1266-1273. DOI: 10.13485/j.cnki.11-2089.2014.0172. ZHANG Zhengpeng, JIANG Wanshou, ZHANG Jing. An Image Match Method Based on Optical Flow Feature Clustering for Vehicle-borne Panoramic Image Sequence[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(12): 1266-1273. DOI: 10.13485/j.cnki.11-2089.2014.0172.
[8] SATO T, PAJDLA T, YOKOYA N. Epipolar Geometry Estimation for Wide-baseline Omnidirectional Street View Images[C]//Proceedings of the 2011 IEEE International Conference on Computer Vision Workshops. Barcelona, Spain: IEEE, 2011: 56-63.
[9] RUPNIK E, NEX F, TOSCHI I, et al. Aerial Multi-camera Systems: Accuracy and Block Triangulation Issues[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 101: 233-246.
[10] KIM J S, HWANGBO M, KANADE T. Motion Estimation Using Multiple Non-overlapping Cameras for Small Unmanned Aerial Vehicles[C]//Proceedings of the 2008 IEEE International Conference on Robotics and Automation. Pasadena, CA, USA: IEEE, 2008: 3076-3081.
[11] 李松. 基于图像拼接的球面全景图研究[D]. 长春: 长春理工大学, 2012. LI Song. Research of Sphere Panorama Based on Image Mosaic[D]. Changchun: Changchun University of Science and Technology, 2012.
[12] IKEDA S, SAT T, YOKOYA N. High-resolution Panoramic Movie Generation from Video Streams Acquired by an Omnidirectional Multi-camera System[C]//Proceedings of the 2003 IEEE International Multisensor Fusion and Integration for Intelligent Systems. Tokyo, Japan: IEEE, 2003: 155-160.
[13] 季顺平, 史云. 车载全景相机的影像匹配和光束法平差[J]. 测绘学报, 2013, 42(1): 94-100, 107. JI Shunping, SHI Yun. Image Matching and Bundle Adjustment Using Vehicle-based Panoramic Camera[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(1): 94-100, 107.
[14] LI Shigang, FUKUMORI K. Spherical Stereo for the Construction of Immersive VR Environment[C]//Proceedings of the 2005 IEEE Virtual Reality. Bonn, Germany: IEEE, 2005: 217-222.
[15] LI Shigang. Binocular Spherical Stereo[J]. IEEE Transactions on Intelligent Transportation Systems, 2008, 9(4): 589-600.
[16] 季顺平, 史云. 多镜头组合型全景相机两种成像模型的定位精度比较[J]. 测绘学报, 2014, 43(12): 1252-1258. DOI: 10.13485/j.cnki.11-2089.2014.0169. JI Shunping, SHI Yun. Comparison of Two Sensor Models for Multi-camera Rig System in Measurements[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(12): 1252-1258. DOI: 10.13485/j.cnki.11-2089.2014.0169.
[17] SHI Yun, JI Shunping, SHI Zhongchao, et al. GPS-supported Visual SLAM with a Rigorous Sensor Model for a Panoramic Camera in Outdoor Environments[J]. Sensors, 2013, 13(1): 119-136.
[18] EBNER H, KORNUS W, OHLHOF T. A Simulation Study on Point Determination for the MOMS-02/D2 Space Project Using an Extended Functional Model[J]. International Archives of Photogrammetry and Remote Sensing, 1993, 29: 458-464.
[19] 张剑清, 潘励, 王树根. 摄影测量学[M]. 2版. 武汉: 武汉大学出版社, 2009. ZHANG Jianqing, PAN Li, WANG Shugen. Photogrammetry[M]. 2nd ed. Wuhan: Wuhan University Press, 2009.
[20] ZHANG Yongjun, XIONG Xiaodong, SHEN Xiang, et al. Bundle Block Adjustment of Weakly Connected Aerial Imagery[J]. Photogrammetric Engineering & Remote Sensing, 2012, 78(9): 983-989.
[21] 张永军, 张勇. 大重叠度影像的相对定向与前方交会精度分析[J]. 武汉大学学报(信息科学版), 2005, 30(2): 126-130. ZHANG Yongjun, ZHANG Yong. Analysis of Precision of Relative Orientation and Forward Intersection with High-overlap Images[J]. Geomatics and Information Science of Wuhan University, 2005, 30(2): 126-130.