Block Motion Model for Optical Flow with Smoothness Prior Function

Author

Tandjung, Stephanus Surijadarma ; Soon, Seah Hock ; Kemao, Qian

Author_Institution

BeyondLSI, Inc., Tokyo

fYear

2006

fDate

5-8 Dec. 2006

Firstpage

1

Lastpage

6

Abstract

An explicit constraint is introduced into the Lucas-Kanade gradient based block motion model. This constraint helps the estimation process to consider surrounding motion vectors during its calculation. Consequently a better motion field can be produced than that by the original block motion model. Further, a discontinuity adaptive function is introduced into the Lucas-Kanade equation, which helps to preserve the discontinuities of motion fields

Keywords

Markov processes; image sequences; maximum likelihood estimation; motion estimation; Lucas-Kanade equation; Lucas-Kanade gradient; Markov random field; block motion model; discontinuity adaptive function; maximum a posterior probability; motion estimation; motion field discontinuity; motion vectors; optical flow; smoothness prior function; Entropy; Equations; Image motion analysis; Image sequences; Markov random fields; Motion control; Motion estimation; Motion measurement; PSNR; Markov random field; maximum a posterior probability; motion estimation; optical flow;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on

Conference_Location

Singapore

Print_ISBN

1-4244-0341-3

Electronic_ISBN

1-4214-042-1

Type

conf

DOI

10.1109/ICARCV.2006.345246

Filename

4150286