DocumentCode :
1191733
Title :
Camera cluster in motion: motion estimation for generalized camera designs
Author :
Pless, Robert
Author_Institution :
Washington Univ., St. Louis, MO, USA
Volume :
11
Issue :
4
fYear :
2004
Firstpage :
39
Lastpage :
44
Abstract :
The first comparison of different types of cameras (as opposed to different algorithms) for the ego-motion estimation problem is presented. As technology and computational power increase, the effectiveness of visual algorithms is limited only by inherent statistical uncertainties in the problems they are solving. The Fisher information matrix is a powerful analysis technique that can apply to any problem that involves searching for a parameter set that minimizes an error function. This includes problems such as pose-estimation, object recognition, or classification. Designing camera systems optimized for particular tasks may significantly improve the success of visual algorithms.
Keywords :
cameras; motion estimation; object recognition; pattern clustering; Fisher information matrix; camera cluster; ego-motion estimation problem; inherent statistical uncertainties; nonpinhole cameras; object recognition; pinhole cameras; pose-estimation; visual algorithms; Algorithm design and analysis; Digital cameras; Eyes; Geometry; Image analysis; Layout; Motion analysis; Motion estimation; Navigation; Robotics and automation;
fLanguage :
English
Journal_Title :
Robotics & Automation Magazine, IEEE
Publisher :
ieee
ISSN :
1070-9932
Type :
jour
DOI :
10.1109/MRA.2004.1371607
Filename :
1371607
Link To Document :
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