Pose Estimation by Fusing Noisy Data of Different Dimensions

Authors:
Yaacov Hel-Or;Michael Werman
Affiliations:
-;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1995

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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.