DocumentCode
1246902
Title
Pose estimation by fusing noisy data of different dimensions
Author
Hel-Or, Yacov ; Werman, Michael
Author_Institution
Inst. of Comput. Sci., Hebrew Univ., Jerusalem, Israel
Volume
17
Issue
2
fYear
1995
fDate
2/1/1995 12:00:00 AM
Firstpage
195
Lastpage
201
Abstract
A method for fusing and integrating different 2D and 3D measurements for pose estimation is proposed. The 2D measured data is viewed as 3D data with infinite uncertainty in particular directions. The method is implemented using Kalman filtering. It is robust and easily parallelizable
Keywords
Kalman filters; filtering theory; object recognition; sensor fusion; 2D measurements; 3D measurement; Kalman filtering; infinite uncertainty; noisy data; pose estimation; Covariance matrix; Filtering; Geometry; Iterative methods; Noise measurement; Object recognition; Particle measurements; Position measurement; Robustness; Solids;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.368169
Filename
368169
Link To Document