NDLI: Estimation of motion parameters for a deformable object from range data

Content Provider	IEEE Xplore Digital Library
Author	Chaudhuri, S. Chatterjee, S.
Copyright Year	1989
Description	Author affiliation: Dept. of Electr. & Comput. Eng., California Univ., San Diego, CA, USA (Chaudhuri, S.; Chatterjee, S.)
Abstract	If the correspondence between two sets of points representing the coordinates of different points of an object undergoing rotational motion and deformation is known, the parameters can be estimated using different least-squares estimators. The total-least-squares (TLS) method is very appropriate when the observation and the data matrices are both perturbed by random noise. For Gaussian-distributed noise, the TLS solution is equivalent to maximum-likelihood estimation. The mean-square error in TLS is always smaller than in an ordinary least-squares (LS) estimator. The scope is analyzed of TLS in estimating the generalized motion parameters, as is the feasibility of decomposing the generalized motion parameters in terms of rotation and deformation parameters. The performance of TLS is compared to that of the LS estimator.<>
Starting Page	291
Ending Page	295
File Size	322014
Page Count	5
File Format	PDF
ISBN	081861952X
ISSN	10636919
DOI	10.1109/CVPR.1989.37863
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-06-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Motion estimation Parameter estimation Least squares approximation Matrix decomposition Least squares methods Maximum likelihood estimation Data engineering Gaussian noise Mean square error methods Motion analysis
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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