Title

Motion Estimation And Segmentation

Authors

Authors

T. Y. Tian;M. Shah

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Mach. Vis. Appl.

Keywords

optical flow; motion boundaries; line process; Markov random fields; mean field techniques; OPTICAL-FLOW; VISUAL-MOTION; FIELDS; PARALLEL; VISION; Computer Science, Artificial Intelligence; Computer Science, ; Cybernetics; Engineering, Electrical & Electronic

Abstract

In the general structure-from-motion (SFM) problem involving several moving objects in a scene, the essential first step is to segment moving objects independently. We attempt to deal with the problem of optical flow estimation and motion segmentation over a pair of images. We apply a mean field technique to determine optical flow and motion boundaries and present a deterministic algorithm. Since motion discontinuities represented by line process are embedded in the estimation of the optical flow, our algorithm provides accurate estimates of optical flow especially along motion boundaries and handles occlusion and multiple motions. We show that the proposed algorithm outperforms other well-known algorithms in terms of estimation accuracy and timing.

Journal Title

Machine Vision and Applications

Volume

9

Issue/Number

1

Publication Date

1-1-1996

Document Type

Article

Language

English

First Page

32

Last Page

42

WOS Identifier

WOS:A1996UX91500005

ISSN

0932-8092

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