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23 January 2012 Hierarchical multi-level image mosaicing for autonomous navigation of UAV
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Proceedings Volume 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques; 830116 (2012) https://doi.org/10.1117/12.910334
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
A novel algorithm for hierarchical multi-level image mosaicing for autonomous navigation of UAV is proposed. The main contribution of the proposed system is the blocking of the error accumulation propagated along the frames, by incrementally building a long-duration mosaic on the fly which is hierarchically composed of short-duration mosaics. The proposed algorithm fulfills the real-time processing requirements in autonomous navigation as follows. 1) Causality: the current output of the mosaicing system depends only on the current and/or previous input frames, contrary to existing offline mosaic algorithms that depend on future input frames as well. 2) Learnability: the algorithm autonomously analyzes/learns the scene characteristics. 3) Adaptability: the system automatically adapts itself to the scene change and chooses the proper methods for feature selection (i.e., the fast but unreliable LKT vs. the slow but robust SIFT). The evaluation of our algorithm with the extensive field test data involving several thousand airborne images shows the significant improvement in processing time, robustness and accuracy of the proposed algorithm.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sangho Park, Debabrata Ghosh, Naima Kaabouch, Ronald A. Fevig, and William Semke "Hierarchical multi-level image mosaicing for autonomous navigation of UAV", Proc. SPIE 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, 830116 (23 January 2012); https://doi.org/10.1117/12.910334
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