DocumentCode
2031743
Title
The mean field theory for image motion estimation
Author
Zhang, J. ; Hanauer, J.
Author_Institution
Electr. Eng. & Comput. Sci. Dept., Wisconsin Univ., Milwaukee, WI, USA
Volume
5
fYear
1993
fDate
27-30 April 1993
Firstpage
197
Abstract
It is shown how the MFT (mean field theory) can be applied to MRF (Markov random field) model-based motion estimation. Specifically, the motion is characterized by a coupled MRF including a displacement field (motion continuity), a line field (motion discontinuity), and a segmentation field (identifying uncovered areas). These fields are estimated by using the MFT. The efficacy of this approach is demonstrated on synthetic and real-world images.<>
Keywords
Markov processes; image segmentation; model-based reasoning; motion estimation; Markov random field; displacement field; efficacy; image motion estimation; line field; mean field theory; model-based motion estimation; segmentation field;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on
Conference_Location
Minneapolis, MN, USA
ISSN
1520-6149
Print_ISBN
0-7803-7402-9
Type
conf
DOI
10.1109/ICASSP.1993.319781
Filename
319781
Link To Document