Abstract
Aerial navigation based on computer vision is a subject in constant development. It aims to identify the localization of an Unmanned Aerial Vehicle based on aerial images captured during flight. This paper employs a fuzzy-based application to identify landmarks, using the ORB algorithm, which uses descriptors for the neighborhood of keypoints to identify specific registered objects on a scene. In Addition to the keypoint matching from ORB, a fuzzy system is used to analyze each match, in order to guarantee the proper identification of the landmark.
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References
Suzuki, T., Amano, Y., Hashizume, T.: Development of a SIFT based monocular EKF-SLAM algorithm for a small unmanned aerial vehicle. In: SICE Annual Conference, pp. 1656–1659 (2011)
Blumenau, A., Ishak, A., Limone, B., Mintz, Z., Russell, C., Sudol, A., Linton, R., Lai, L., Padir, T., Van Hook, R.: Design and implementation of an intelligent portable aerial surveillance system (ipass). In: Technologies for Practical Robot Applications (TePRA), pp. 1–6 (2013)
Suzuki, T., Amano, Y., Hashizume, T.: Vision based localization of a small UAV for generating a large mosaic image. In: SICE Annual Conference, pp. 2960–2964 (2010)
Liu, Y.C., Dai, Q.H.: Vision aided unmanned aerial vehicle autonomy: An overview. In: Image and Signal Processing (CISP), pp. 417–421 (2010)
Zhao, X., Fei, Q., Geng, Q.: Vision based ground target tracking for rotor uav. In: Control and Automation (ICCA), pp. 1907–1911 (2013)
Dumble, S., Gibbens, P.: Efficient terrain-aided visual horizon based attitude estimation and localization. Journal of Inteligent and Robotic Systems (2014)
Rady, S., Kandil, A., Badreddin, E.: A hybrid localization approach for UAV in GPS denied areas. In: International Symposium on System Integration (SII), pp. 1269–1274 (2011)
Guan, X., Bai, H.: A GPU accelerated real-time self-contained visual navigation system for UAVs. In: International Conference on Information and Automation (ICIA), pp. 578–581 (2012)
Bodensteiner, C., Hübner, W., Jüngling, K., Solbrig, P., Arens, M.: Monocular camera trajectory optimization using LiDAR data. In: Computer Vision Workshops (ICCV), pp. 2018–2025 (2011)
Lee, L., An, S., Oh, S.: Effective visual salient object landmark extraction and recognition. IEEE Systems, Man, and Cybernetics, 1351–1357 (2011)
Kwon, H., Sharma, R., Yoder, J., Pack, D.: Robust mobile ground target localization using ground image features with UAV position compensation techniques. In: International Conference on Control, Automation and Systems (ICCAS), pp. 454–458 (2012)
Rublee, E., Garage, W., Park, M., Rabaud, V., Konolige, K., Bradski, G.: Orb: An efficient alternative to sift or surf. In: International Conference on Computer Vision (ICCV), pp. 2564–2571 (2011)
Zimmermann, J.: Fuzzy set theory and its applications, 4th edn. (2001)
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Filho, P.S., Rodrigues, M., Saotome, O., Shiguemori, E.H. (2014). Fuzzy-Based Automatic Landmark Recognition in Aerial Images Using ORB for Aerial Auto-localization. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8887. Springer, Cham. https://doi.org/10.1007/978-3-319-14249-4_44
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DOI: https://doi.org/10.1007/978-3-319-14249-4_44
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14248-7
Online ISBN: 978-3-319-14249-4
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