Statistical bias of conic fitting and renormalization
Kanatani, K.
Dept. of Comput. Sci., Gunma Univ.;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Mar 1994
Volume: 16,
Issue: 3
On page(s): 320-326
ISSN: 0162-8828
References Cited: 22
CODEN: ITPIDJ
INSPEC Accession Number: 4679820
Digital Object Identifier: 10.1109/34.276132
Current Version Published: 2002-08-06
Abstract
Introducing a statistical model of noise in terms of the
covariance matrix of the N-vector, we point out that the least-squares
conic fitting is statistically biased. We present a new fitting scheme
called renormalization for computing an unbiased estimate by
automatically adjusting to noise. Relationships to existing methods are
discussed, and our method is tested using real and synthetic data
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