Fast terrain mapping from low altitude digital imagery

Neurocomputing

Volumn 156, Issue , 2015, Pages 105-116

  Luo, Yawei ^a   Guan, Tao ^a   Wei, Benchang ^a   Pan, Hailong ^a   Yu, Junqing ^a  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Aerial triangulation; Large scale modeling; MAV; Structure from motion; Terrain reconstruction

Indexed keywords

AERIAL PHOTOGRAPHY; ANTENNAS; FIXED WINGS; GLOBAL POSITIONING SYSTEM; IMAGE ENHANCEMENT; LANDFORMS; MICRO AIR VEHICLE (MAV); TRIANGULATION;

AERIAL TRIANGULATION; AIR-BORNE SENSORS; LARGE-SCALE MODELING; LARGE-SCALE TERRAIN; MICRO AERIAL VEHICLE; STATE-OF-THE-ART ALGORITHMS; STATE-OF-THE-ART PERFORMANCE; STRUCTURE FROM MOTION;

IMAGE RECONSTRUCTION;

ALGORITHM; ALTITUDE; ARTICLE; CALCULATION; DIGITAL IMAGING; GEOGRAPHY; IMAGE PROCESSING; IMAGE QUALITY; IMAGE RECONSTRUCTION; MATHEMATICAL COMPUTING; PRIORITY JOURNAL; THREE DIMENSIONAL IMAGING;

EID: 84923532689     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.12.079     Document Type: Article

References (31)

1. C. Wu, Towards linear-time incremental structure from motion, in: Proceedings of the 2013 IEEE International Conference on 3DTV-Conference, 2013, pp. 127-134.
2. Hartley R., Zisserman A. Multiple view geometry in computer vision[M] 2003, 271-284. Cambridge university press.
3. Sinha S.N., Frahm J.M., Pollefeys M., et al. GPU-based video feature tracking and matching[C]//EDGE. Workshop Edge Comput. Using New Commod. Archit. 2006, 278:4321.
4. Pollefeys M., Nistér D., Frahm J.M., et al. Detailed real-time urban 3d reconstruction from video. Int. J. Comput. Vis. 2008, 78(2-3):143-167.
5. Nistér D., Naroditsky O., Bergen J. Visual odometry for ground vehicle applications. J. Field Robot. 2006, 23(1):3-20.
6. Davison A.J., Murray D.s.W. Simultaneous localization and map-building using active vision. IEEE Trans. Pattern Anal. Mach. Intell. 2002, 24(7):865-880.
7. Lobo J., Dias J. Relative pose calibration between visual and inertial sensors. Int. J. Robot. Res. 2007, 26(6):561-575.
8. D. Crandall, A. Owens, N. Snavely, et al. Discrete-continuous optimization for large-scale structure from motion, in: Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3001-3008.
9. Li M., Mourikis A.I. High-precision consistent EKF-based visual-inertial odometry. Int. J. Robot. Res. 2013, 32(6):690-711.
10. M. Li, A.I. Mourikis, Improving the accuracy of EKF-based visual-inertial odometry, in: Proceedings of the 2012 IEEE International Conference on Robotics and Automation (ICRA), 2012, pp. 828-835.
11. M. Maurer, M. Rumpler, A. Wendel, C. Hoppe, A. Irschara, H. Bischof., Geo-referenced 3d reconstruction: fusing public geographic data and aerial imagery, in: Proceedings of the ICRA, 2012.
12. M. Tamaazousti, V. Gay-Bellile, S. Naudet-Collette, S. Bourgeois, M. Dhome., Nonlinear refinement of structure from motion reconstruction by taking advantage of a partial knowledge of the environment, in: Proceedings of the CVPR, 2011.
13. Fischler M.A., Bolles R.C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 1981, 24(6):381-395.
14. M. Jancosek, T. Pajdla, Multi-view reconstruction preserving weakly-supported surfaces, in: Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011, pp. 3121-3128.
15. "Meshlab," . http://sourceforge.net/projects/meshlab/.
16. Agarwal S., Furukawa Y., Snavely N., et al. Building rome in a day. Commun. ACM 2011, 54(10):105-112.
17. N. Snavely, S.M. Seitz, R. Szeliski, Skeletal graphs for efficient structure from motion, in: Proceedings of the CVPRvol. 1, 2008, p. 2.
18. S. Weiss, M.W. Achtelik, S. Lynen, M. Chli, R. Siegwart, Realtime onboard visual-inertial state estimation and self-calibration of mavs in unknown environments, in: Proceedings of the IEEE International Conference on Robotics and Automations, Saint Paul, MN, May 2012, pp. 957-964.
19. Warren M., Mckinnon D., He H., et al. Large Scale Monocular Vision-only Mapping from a Fixed-Wing sUAS[C]//Field and Service Robotics 2014, 495-509. Springer, Berlin, Heidelberg.
20. L. Heng, G.H. Lee, F. Fraundorfer, et al., Real-time photo-realistic 3D mapping for micro aerial vehicles, in: Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2011, pp. 4012-4019.
21. F. Fraundorfer, L. Heng, D. Honegger, et al., Vision-based autonomous mapping and exploration using a quadrotor MAV, in: Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012, pp. 4557-4564.
22. S. Shen, Y. Mulgaonkar, N. Michael, et al., Vision-based state estimation for autonomous rotorcraft MAVs in complex environments, in: Proceedings of the 2013 IEEE International Conference on Robotics and Automation (ICRA), 2013, pp. 1758-1764.
23. B. Triggs, P.F. McLauchlan, R. Hartley, A.W. Fitzgibbon, Bundle adjustment - a modern synthesis, in: Proceedings of the International Workshop Vision Algorithms: Theory and Practice, 2000.
24. Mouragnon E., Lhuillier M., Dhome M., Dekeyser F., Sayd P. Generic and real-time structure from motion using local bundle adjustment. Image Vis. Comput. 2009, 27:1178-1193.
25. C.Wu, S.Agarwal, B.Curless, S.M.Seitz, Multicore bundle adjustment, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011.
26. S. Agarwal, N. Snavely, S.M. Seitz, R. Szeliski, Bundle Adjustment in the Large, in: Proceedings of the European Conference on Computer Vision, 2010.
27. H. Kume, T. Takemoti, T. Sato, N. Yokoya, Extrinsic camera parameter estimation using video images and GPS considering GPS position accuracy, in: Proceedings of the International Conference on Pattern Recognition, 2010.
28. J. Michot, A. Bartoli, F. Gaspard, Bi-objective bundle adjustment with application to multi-sensor slam, in: Proceedings of the International Symposium on 3D Data Processing, Visualization, and Transmission, 2010.
29. Lhuillier M. Incremental fusion of structure-from-motion and gps using constrained bundle adjustments. IEEE Trans. Pattern Anal. Mach. Intell. 2012, 34(12):2489-2495.
30. Ji R., Gao Y., Zhong B., et al. Mining flickr landmarks by modeling reconstruction sparsity. ACM Trans. Multimed. Comput. Commun. Appl. (TOMCCAP) 2011, 7(1):31.
31. Gao Y., Wang M., Ji R., Wu X., Dai Q. 3D object retrieval with Hausdorff distance learning. IEEE Trans Ind. Electron. 2014, 61(4):2088-2098.