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ICRA
2010
IEEE

Maximum likelihood mapping with spectral image registration

13 years 2 months ago
Maximum likelihood mapping with spectral image registration
Abstract— A core challenge in probabilistic mapping is to extract meaningful uncertainty information from data registration methods. While this has been investigated in ICP-based scan matching methods, other registration methods have not been analyzed. In this paper, an uncertainty analysis of a Fourier Mellin based image registration algorithm is introduced, which to our knowledge is the first of its kind involving spectral registration. A covariance matrix is extracted from the result of a Phase-Only Matched Filter, which is interpreted as a probability mass function. The method is embedded in a pose graph implementation for Simultaneous Localization and Mapping (SLAM) and validated with experiments in the underwater domain. published in: International Conference on Robotics and Automation (ICRA), IEEE Press, 2010
Max Pfingsthorn, Andreas Birk 0002, Sören Sch
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where ICRA
Authors Max Pfingsthorn, Andreas Birk 0002, Sören Schwertfeger, Heikow Bülow, Kaustubh Pathak
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