An Overview on “Cloud Control” Photogrammetry in Big Data Era

doi:10.11947/j.AGCS.2017.20170337

Abstract

Abstract: In the present era of big data, photogrammetric image collection modes are characterized with the progressive course of diversity, efficiency and facilitation, which are producing large sets of photogrammetric image data. They further bring the request for advanced processing with higher level of efficiency, automation and intelligence. However, the efficiency of fundamental photogrammetric processing, known as geometric positioning, is still majorly restricted to control points acquired through complex and inefficient field works. In view of this problem, we promote the concept of "cloud control" photogrammetry, which regards geo-encoded data as geometric control instead of field control points, and is achieved via control information extraction with extensive and intensive automatic matching (or registration) technology. Three control modes will be introduced, considered as image-based-control, vector-map-based-control and LiDAR-point-based-control respectively. By the end of the paper, we provide the discussion on the application prospects and foreseeable problems of "cloud control" photogrammetry.

Key words: photogrammetric big data, “cloud control” photogrammetry, cloud control information extraction

CLC Number:

P227

ZHANG Zuxun, TAO Pengjie. An Overview on “Cloud Control” Photogrammetry in Big Data Era[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1238-1248.

References

[1] HILBERT M. Big Data for Development:A Review of Promises and Challenges[J]. Development Policy Review, 2016, 34(1):135-174.
[2] 陈鲸. 大数据面临的挑战复杂艰巨[J]. 信息安全与通信保密, 2016(2):20. CHEN Jing. Big Data Faces Complex and Arduous Challenges[J]. Information Security and Communications Privacy, 2016(2):20.
[3] LOWE D G. Distinctive Image Features from Scale-invariant Key Points[J]. International Journal of Computer Vision, 2004, 60(2):91-110.
[4] BORE N, AMBRUS R, JENSFELT P, et al. Efficient Retrieval of Arbitrary Objects from Long-term Robot Observations[J]. Robotics and Autonomous Systems, 2017,91:139-150.
[5] SCHÖNBERGER J L, FRAHM J M. Structure-from-motion Revisited[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, NV:IEEE, 2016:4104-4113.
[6] FRASER C S. Digital Camera Self-calibration[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 1997, 52(4):149-159.
[7] BRITO J H, ANGST R, KÖSER K, et al. Radial Distortion Self-Calibration[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Portland, OR:IEEE, 2013:1368-1375.
[8] ZHANG Zuxun, LU Luping, TAO Pengjie, et al. Registration of CBERS-02B Satellite Imagery in Quick GIS Updating[C]//Proceedings of SPIE, Remote Sensing Image Processing, Geographic Information Systems, and Other Applications. Guilin, China:SPIE, 2011:8006OC.
[9] ZHENG Shunyi, HUANG Rongyong, ZHOU Yang. Registration of Optical Images with Lidar Data and Its Accuracy Assessment[J]. Photogrammetric Engineering & Remote Sensing, 2013, 79(8):731-741.
[10] CHEN Jun, DOWMAN Ian, LI Songnian, et al. Information from Imagery:ISPRS Scientific Vision and Research Agenda[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016,115:3-21.
[11] AXELSSON P. Processing of Laser Scanner Data:Algorithms and Applications[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 1999, 54(2-3):138-147.
[12] ZHANG Yongjun, ZHENG Maoteng, XIONG Jinxin, et al. On-orbit Geometric Calibration of ZY-3 Three-line Array Imagery with Multistrip Data Sets[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(1):224-234.
[13] TAO Pengjie, LU Luping, ZHANG Yong, et al. On-orbit Geometric Calibration of the Panchromatic/Multispectral Camera of the ZY-102C Satellite Based on Public Geographic Data[J]. Photogrammetric Engineering & Remote Sensing, 2014, 80(6):505-517.
[14] 张祖勋, 张剑清. 广义点摄影测量及其应用[J]. 武汉大学学报(信息科学版), 2004, 30(1):1-5. ZHANG Zuxun, ZHANG Jianqing. Generalized Point Photogrammetry and Its Application[J]. Geomatics and Information Science of Wuhan University, 2004, 30(1):1-5.
[15] 张宏伟. 矢量与遥感影像的自动配准[D]. 武汉:武汉大学, 2004. ZHANG Hongwei. Automatic Registration between Remote Sensing Image and Vector Map[D]. Wuhan:Wuhan University, 2004.
[16] ZOU Songbai, ZHANG Jianqing, ZHANG Yong. The Automatic Registration between High Resolution Satellite Images and a Vector Map Based on RFM[C]//Proceedings of IEEE International Conference on Image Analysis and Signal Processing. Taizhou:IEEE, 2009:397-401.
[17] LU Luping, ZHANG Yong, TAO Pengjie, et al. Estimation of Transformation Parameters between Centre-line Vector Road Maps and High Resolution Satellite Images[J]. The Photogrammetric Record, 2013, 28(142):130-144.
[18] MAY N C, TOTH C K. Point Positioning Accuracy of Airborne LiDAR Systems:A Rigorous Analysis[J]. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. 2007,36:107-111.
[19] AGUILAR F J, MILLS J P. Accuracy Assessment of LiDAR-derived Digital Elevation Models[J]. The Photogrammetric Record, 2008, 23,122:148-169.
[20] RAY J A, GRAHAM L. New Horizontal Accuracy Assessment Tools and Techniques for LiDAR Data[C]//Proceedings of the ASPRS 2008 Annual Conference. Portland, Oregon:[s.n.], 2008.
[21] 熊小东. 基于多种特征的机载激光点云与航空影像配准方法研究[D]. 武汉:武汉大学, 2014. XIONG Xiaodong. Registration of Airborne LiDAR Point Cloud and Aerial Images Using Multi-features[D]. Wuhan:Wuhan University, 2014.
[22] BESL P J, MCKAY N D. A Method for Registration of 3-D Shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(2):239-256.
[23] RUSU R B, BLODOW N, BEETZ M. Fast Point Feature Histograms (FPFH) for 3D Registration[C]//Proceedings of IEEE International Conference on Robotics and Automation. Kobe:IEEE, 2009:3212-3217.
[24] HABIB A, GHANMA M, Morgan M, et al. Photogrammetric and LiDAR Data Registration Using Linear Features[J]. Photogrammetric Engineering & Remote Sensing, 2005, 71(6):699-707.
[25] HABIB A, SHIN S, KIM C, et al. Integration of Photogrammetric and LiDAR Data in a Multi-primitive Triangulation Environment[C]//Innovations in 3D Geo Information Systems, First International Workshop on 3D Geoinformation. Kuala Lumpur, Malaysia:DBLP, 2006:29-45.
[26] 杜全叶. 无地面控制的航空影像与LiDAR数据自动高精度配准[D]. 武汉:武汉大学, 2010. DU Quanye. Automatic High Precision Registration between Aerial Images and LiDAR Data without Ground Control Points[D]. Wuhan:Wuhan University, 2010.
[27] 黄荣永. 多元数据几何配准方法与应用研究[D]. 武汉:武汉大学, 2015. HUANG Rongyong. Research on Geometric Registration Methods of Multiple Photogrammetric Data and Their Applications[D]. Wuhan:Wuhan University, 2015.
[28] 维克托·迈尔-舍恩伯格, 肯尼思·库克耶. 大数据时代:生活、工作与思维的大变革[M]. 盛杨燕, 周涛, 译. 杭州:浙江人民出版社, 2013. MAYER-SCHONBERGER V, CUKIER K. Big Data:A Revolution that Will Transform How We Live, Work and Think[M]. SHENG Yangyan, ZHOU Tao, trans. Hangzhou:Zhejiang People's Publishing House, 2013.