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