Analytic solutions for multiple motions

Author

Mota, C. ; Stuke, I. ; Barth, E.

Author_Institution

Inst. for Signal Process., Univ. of Lubeck, Germany

Volume

2

fYear

2001

Firstpage

917

Abstract

A novel framework for single and multiple motion estimation is presented. It is based on a generalized structure tensor that contains blurred products of directional derivatives. The order of differentiation increases with the number of motions but more general linear filters can be used instead of derivatives. From the general framework, a hierarchical algorithm for motion estimation is derived and its performance is demonstrated on a synthetic sequence

Keywords

computational complexity; computer vision; differentiation; eigenvalues and eigenfunctions; filtering theory; image sequences; motion estimation; analytic solutions; blurred products; computer vision; differentiation order; directional derivatives; eigenvectors; general linear filters; generalized structure tensor; hierarchical algorithm; low-complexity algorithms; medical imaging; multiple motion estimation; synthetic image sequence; Computer applications; Eigenvalues and eigenfunctions; Gabor filters; Least squares approximation; Motion analysis; Motion estimation; Nonlinear filters; Optimization methods; Signal processing; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2001. Proceedings. 2001 International Conference on

Conference_Location

Thessaloniki

Print_ISBN

0-7803-6725-1

Type

conf

DOI

10.1109/ICIP.2001.958644

Filename

958644