Title
Motion Estimation And Segmentation
Keywords
Line process; Markov random fields; Mean field techniques; Motion boundaries; Optical flow
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.
Publication Date
1-1-1996
Publication Title
Machine Vision and Applications
Volume
9
Issue
1
Number of Pages
32-42
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/BF01246637
Copyright Status
Unknown
Socpus ID
0029696180 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0029696180
STARS Citation
Tian, Tina Yu and Shah, Mubarak, "Motion Estimation And Segmentation" (1996). Scopus Export 1990s. 2445.
https://stars.library.ucf.edu/scopus1990/2445