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 s...Show MoreMetadata
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.
Date of Conference: 03-07 May 2010
Date Added to IEEE Xplore: 15 July 2010
ISBN Information:
Print ISSN: 1050-4729
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Image Registration ,
- Maximum Likelihood Mapping ,
- Spectral Registration ,
- Covariance Matrix ,
- Uncertainty Information ,
- Registration Method ,
- Registration Algorithm ,
- Simultaneous Localization And Mapping ,
- Image Registration Algorithm ,
- Fourier Transform ,
- Objective Function ,
- Optimization Algorithm ,
- Parameter Space ,
- Scale Parameter ,
- Sensor Data ,
- Camera Images ,
- Kinds Of Data ,
- Proper Localization ,
- Image Frames ,
- Mahalanobis Distance ,
- Registration Results ,
- Rotation Parameters ,
- Odometry ,
- Intel Core I7 ,
- Vertices ,
- Functional Framework ,
- Part Of The Map ,
- Shift Of Signal ,
- Loop Closure ,
- Loop Detection
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Image Registration ,
- Maximum Likelihood Mapping ,
- Spectral Registration ,
- Covariance Matrix ,
- Uncertainty Information ,
- Registration Method ,
- Registration Algorithm ,
- Simultaneous Localization And Mapping ,
- Image Registration Algorithm ,
- Fourier Transform ,
- Objective Function ,
- Optimization Algorithm ,
- Parameter Space ,
- Scale Parameter ,
- Sensor Data ,
- Camera Images ,
- Kinds Of Data ,
- Proper Localization ,
- Image Frames ,
- Mahalanobis Distance ,
- Registration Results ,
- Rotation Parameters ,
- Odometry ,
- Intel Core I7 ,
- Vertices ,
- Functional Framework ,
- Part Of The Map ,
- Shift Of Signal ,
- Loop Closure ,
- Loop Detection