TY - GEN

T1 - Parametric estimation of multi-dimensional affine transformations in the presence of noise

T2 - 2005 IEEE/SP 13th Workshop on Statistical Signal Processing

AU - Hagege, Rami

AU - Francos, Joseph M.

PY - 2005/1/1

Y1 - 2005/1/1

N2 - We consider the general framework of planar object registration and recognition based on a set of known templates. While the set of templates Is known, the tremendous set of possible affine transformations that may relate the template and the observed signature, makes any detection and recognition problem Ill-defined unless this variability Is taken Into account. Given a noisy observation on one of the known objects, subject to an unknown affine transformation of It, our goal Is to estimate the deformation that transforms some prechosen representation of this object (template) Into the current observation. We propose a method that employs a set of non-linear operators to replace the original high dimensional and non-linear problem by an equivalent linear least-squares problem, expressed In terms of the unknown affine transformation parameters. The proposed solution Is unique and Is applicable to any affine transformation regardless of the magnitude of the deformation.

AB - We consider the general framework of planar object registration and recognition based on a set of known templates. While the set of templates Is known, the tremendous set of possible affine transformations that may relate the template and the observed signature, makes any detection and recognition problem Ill-defined unless this variability Is taken Into account. Given a noisy observation on one of the known objects, subject to an unknown affine transformation of It, our goal Is to estimate the deformation that transforms some prechosen representation of this object (template) Into the current observation. We propose a method that employs a set of non-linear operators to replace the original high dimensional and non-linear problem by an equivalent linear least-squares problem, expressed In terms of the unknown affine transformation parameters. The proposed solution Is unique and Is applicable to any affine transformation regardless of the magnitude of the deformation.

UR - http://www.scopus.com/inward/record.url?scp=33947158747&partnerID=8YFLogxK

U2 - 10.1109/ssp.2005.1628563

DO - 10.1109/ssp.2005.1628563

M3 - Conference contribution

AN - SCOPUS:33947158747

SN - 0780394046

SN - 9780780394049

T3 - IEEE Workshop on Statistical Signal Processing Proceedings

SP - 55

EP - 58

BT - 2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Book of Abstracts

PB - Institute of Electrical and Electronics Engineers

Y2 - 17 July 2005 through 20 July 2005

ER -