A PSEUDO 3D motion estimator for moving object estimation in noisy video sequences

Author

Topping, Christopher L. ; Chambers, Jonathon A.

Author_Institution

Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK

fYear

1998

fDate

8-11 Sept. 1998

Firstpage

1

Lastpage

4

Abstract

This paper presents a three-dimensional motion estimator for use in cases where we have noisy video sequences containing one moving object on a stationary background. The motion estimator is to be used as part of an image enhancing pre-processing step. A Parallel Extended Kalman Filter (PEKF) developed by J. B. Burl is at the heart of this motion estimator, together with additional data mapping techniques for its expansion to what is referred to as a Pseudo 3D motion estimator. This motion estimator is shown with simulations to have much potential for object motion estimation at low image SNR levels, (<; 5dB).

Keywords

Kalman filters; image enhancement; image sequences; motion estimation; video signal processing; PEKF; data mapping techniques; image SNR levels; image enhancing preprocessing step; moving object motion estimation; noisy video sequences; parallel extended Kalman filters; pseudo 3D motion estimator; stationary background; three-dimensional motion estimator; Correlation; Estimation; Mathematical model; Motion compensation; Motion estimation; Noise; Three-dimensional displays;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference (EUSIPCO 1998), 9th European

Conference_Location

Rhodes

Print_ISBN

978-960-7620-06-4

Type

conf

Filename

7090015