On div-curl regularization for motion estimation in 3-D volumetric imaging

Author

Gupta, Sandeep N. ; Prince, Jerry L.

Author_Institution

Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA

Volume

1

fYear

1996

fDate

16-19 Sep 1996

Firstpage

929

Abstract

We consider the classical optical flow algorithm due to Horn and Schunck (1981) for estimating the motion of brightness patterns between image pairs. We use a modified smoothness condition based on the divergence and curl of the velocity field. In previous work, we have developed well-posed stochastic state-space models for these optical flow methods in two dimensions. This paper extends our results to 3-D. We first show that by using the first order div-curl spline, it is not possible to obtain a first order linear differential well-posed model in 3-D. Next, we employ the second order div-curl spline smoothness condition and develop well-posed state-space models

Keywords

brightness; image sequences; linear differential equations; motion estimation; smoothing methods; splines (mathematics); state-space methods; stochastic processes; 3D volumetric imaging; brightness patterns; curl; div-curl regularization; divergence; first order div-curl spline; first order linear differential well-posed model; image pairs; modified smoothness condition; motion estimation; optical flow algorithm; optical flow methods; second order div-curl spline smoothness; stochastic state-space models; velocity field; well-posed state-space models; Brightness; Image motion analysis; Image sequence analysis; Laboratories; Motion estimation; Optical computing; Optical imaging; Spline; State-space methods; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1996. Proceedings., International Conference on

Conference_Location

Lausanne

Print_ISBN

0-7803-3259-8

Type

conf

DOI

10.1109/ICIP.1996.559652

Filename

559652