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Proceedings Paper

Hierarchical multi-level image mosaicing for autonomous navigation of UAV
Author(s): Sangho Park; Debabrata Ghosh; Naima Kaabouch; Ronald A. Fevig; William Semke
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Paper 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.

Paper Details

Date Published: 23 January 2012
PDF: 9 pages
Proc. SPIE 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, 830116 (23 January 2012); doi: 10.1117/12.910334
Show Author Affiliations
Sangho Park, The Univ. of North Dakota (United States)
Debabrata Ghosh, The Univ. of North Dakota (United States)
Naima Kaabouch, The Univ. of North Dakota (United States)
Ronald A. Fevig, The Univ. of North Dakota (United States)
William Semke, The Univ. of North Dakota (United States)


Published in SPIE Proceedings Vol. 8301:
Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques
Juha Röning; David P. Casasent, Editor(s)

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