Real-Time UAV Global Pose Estimation Using 3D Terrain Engine
Keywords:
UAV, Pose Estimation, 3D Terrain Engine, Local Features,Abstract
We present a new approach that automatically estimates global pose for a UAV in real-time using 3D terrain engine. Inaccurate auxiliary sensors on the UAV were used to obtain initial real camera pose that moves the virtual camera inside the 3D terrain engine. We, then automatically found multiple matches between the two images to find the 3D coordinates of the matches using the 3D terrain engine. Finally, we tested the co-planarity of the 3D points under the camera, depending on this test. We used coplanar or non-coplanar algorithm to estimate accurate global camera pose. We executed feature detection, description and pair wise matching algorithms on GPU to get a suitable frame rate (12 FPS) needed in the navigation applications. The proposed approach has been tested on a synthetic and real data. Experimental results proved the feasibility and robustness of the proposed approach, and the precision was the same order as the 3D terrain engine used. Finally, we can say that the 3D terrain engine succeeded when other methods failed.
References
Son K.-H., Hwang Y., and Kweon I. S., “Uav global pose estimation by matching forward-looking aerial images with satellite images,” in Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on. IEEE, pp. 3880–3887, 2009.
Lowe D. G., “Distinctive image features from scale-invariant keypoints,” International journal of computer vision, vol. 60, no. 2, pp. 91–110, 2004.
Bay H., Ess A., Tuytelaars T., and Van Gool L., “Speeded-up robust features (surf) ,” Computer vision and image understanding, vol. 110, no. 3, pp. 346–359, 2008.
Lim H., Sinha S. N., Cohen M. F., and Uyttendaele M., “Realtime image-based 6-dof localization in large-scale environments,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2012), June 2012.
Haralick B. M., Lee C.-N., Ottenberg K., and Nolle M., “Review and analysis of solutions of the three point perspective pose estimation problem,” International journal of computer vision, vol. 13, no. 3, pp. 331–356, 1994.
Lourakis M. and Zabulis X., “Model-based pose estimation for rigid objects,” in Computer Vision Systems. Springer, pp. 83–92, 2013.
Snyder J. P., “Map projections–A working manual,” US Government
Printing Office, pp. 1395, 1987.
Irschara A., Kaufmann V., Klopschitz M., Bischof H., and Leberl F., Towards fully automatic photogrammetric reconstruction using digital images taken from UAVs. Na, 2010.
Heikkila J. and Silven O., “A four-step camera calibration procedure with implicit image correction,” in Computer Vision and Pattern Recognition Proceedings, IEEE Computer Society Conference on. IEEE, pp. 1106–1112, 1997.
Lingua A., Marenchino D., and Nex F., “Performance analysis of the sift operator for automatic feature extraction and matching in photogrammetric applications,” Sensors, vol. 9, no. 5, pp. 3745–3766, 2009.
Mikolajczyk K., Tuytelaars T., Schmid C., Zisserman A., Matas J., Schaffalitzky F., Kadir T., and Van Gool L., “A comparison of affine region detectors,” International journal of computer vision, vol. 65, no. 1-2, pp. 43–72, 2005.
Silpa-Anan C. and Hartley R., “Optimised kd-trees for fast image descriptor matching,” in Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pp. 1–8, 2008.
Muja M. and Lowe D. G., “Fast approximate nearest neighbors with automatic algorithm configuration,” VISAPP, vol. 2, no. 1, 2009.
Petersen T., A comparison of 2d-3d pose estimation methods. Master’s thesis, Aalborg University-Institute for Media Technology Computer Vision and Graphics, Lautrupvang, vol. 15, pp. 2750.
Fischler M. A. and Bolles R. C., “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Communications of the ACM, vol. 24, no. 6, pp. 381–395, 1981.
Zhang Z., “A flexible new technique for camera calibration,”
Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 22, no. 11, pp. 1330–1334, 2000.
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