Fine estimators of two-dimensional parameters and application to spatial shift estimation

Author

Giunta, Gaetano

Author_Institution

INFOCOM Dept., Rome Univ., Italy

Volume

47

Issue

12

fYear

1999

fDate

12/1/1999 12:00:00 AM

Firstpage

3201

Lastpage

3207

Abstract

This paper presents a fast technique for fine estimation of two-dimensional (2-D) parameters, based on a parabolic interpolation of the same ambiguity function samples, and aimed at block-oriented estimation of the spatial shift between pairs of images in video sequences. Expressions for the bias and variance of the position error and the prediction error are derived. The method is tested using a synthetically generated autocorrelation function, varying the directionality and the eccentricity factor, in order to compare the performance of the proposed 2-D estimator to the case of two separate one-dimensional (1-D) estimators. The method has also been applied in vision systems, evidencing encouraging results for estimating the parameters of sophisticated global motion models from real images

Keywords

computer vision; correlation methods; error analysis; image motion analysis; image sampling; image sequences; interpolation; parameter estimation; prediction theory; video signal processing; 1D estimator; 2D parameter estimation; ambiguity function samples; block-oriented estimation; eccentricity factor; fast technique; fine estimation; global motion models; parabolic interpolation; position error bias; position error variance; prediction error; real images; spatial shift; spatial shift estimation; synthetically generated autocorrelation function; video sequences; vision systems; Displacement measurement; Image storage; Interpolation; Machine vision; Maximum likelihood estimation; Motion analysis; Motion estimation; Parameter estimation; Testing; Video sequences;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.806066

Filename

806066