---
_id: '3185'
abstract:
- lang: eng
text: This paper describes models and algorithms for the real-time segmentation
of foreground from background layers in stereo video sequences. Automatic separation
of layers from color/contrast or from stereo alone is known to be error-prone.
Here, color, contrast, and stereo matching information are fused to infer layers
accurately and efficiently. The first algorithm, Layered Dynamic Programming (LDP),
solves stereo in an extended six-state space that represents both foreground/background
layers and occluded regions. The stereo-match likelihood is then fused with a
contrast-sensitive color model that is learned on-the-fly and stereo disparities
are obtained by dynamic programming. The second algorithm, Layered Graph Cut (LGC),
does not directly solve stereo. Instead, the stereo match likelihood is marginalized
over disparities to evaluate foreground and background hypotheses and then fused
with a contrast-sensitive color model like the one used in LDP. Segmentation is
solved efficiently by ternary graph cut. Both algorithms are evaluated with respect
to ground truth data and found to have similar performance, substantially better
than either stereo or color/contrast alone. However, their characteristics with
respect to computational efficiency are rather different. The algorithms are demonstrated
in the application of background substitution and shown to give good quality composite
video output.
author:
- first_name: Vladimir
full_name: Vladimir Kolmogorov
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Antonio
full_name: Criminisi, Antonio
last_name: Criminisi
- first_name: Andrew
full_name: Blake, Andrew
last_name: Blake
- first_name: Geoffrey
full_name: Cross, Geoffrey
last_name: Cross
- first_name: Carsten
full_name: Rother, Carsten
last_name: Rother
citation:
ama: Kolmogorov V, Criminisi A, Blake A, Cross G, Rother C. Probabilistic fusion
of stereo with color and contrast for bilayer segmentation. IEEE Transactions
on Pattern Analysis and Machine Intelligence. 2006;28(9):1480-1492. doi:10.1109/TPAMI.2006.193
apa: Kolmogorov, V., Criminisi, A., Blake, A., Cross, G., & Rother, C. (2006).
Probabilistic fusion of stereo with color and contrast for bilayer segmentation.
IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2006.193
chicago: Kolmogorov, Vladimir, Antonio Criminisi, Andrew Blake, Geoffrey Cross,
and Carsten Rother. “Probabilistic Fusion of Stereo with Color and Contrast for
Bilayer Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence.
IEEE, 2006. https://doi.org/10.1109/TPAMI.2006.193.
ieee: V. Kolmogorov, A. Criminisi, A. Blake, G. Cross, and C. Rother, “Probabilistic
fusion of stereo with color and contrast for bilayer segmentation,” IEEE Transactions
on Pattern Analysis and Machine Intelligence, vol. 28, no. 9. IEEE, pp. 1480–1492,
2006.
ista: Kolmogorov V, Criminisi A, Blake A, Cross G, Rother C. 2006. Probabilistic
fusion of stereo with color and contrast for bilayer segmentation. IEEE Transactions
on Pattern Analysis and Machine Intelligence. 28(9), 1480–1492.
mla: Kolmogorov, Vladimir, et al. “Probabilistic Fusion of Stereo with Color and
Contrast for Bilayer Segmentation.” IEEE Transactions on Pattern Analysis and
Machine Intelligence, vol. 28, no. 9, IEEE, 2006, pp. 1480–92, doi:10.1109/TPAMI.2006.193.
short: V. Kolmogorov, A. Criminisi, A. Blake, G. Cross, C. Rother, IEEE Transactions
on Pattern Analysis and Machine Intelligence 28 (2006) 1480–1492.
date_created: 2018-12-11T12:01:53Z
date_published: 2006-09-01T00:00:00Z
date_updated: 2021-01-12T07:41:39Z
day: '01'
doi: 10.1109/TPAMI.2006.193
extern: 1
intvolume: ' 28'
issue: '9'
main_file_link:
- open_access: '0'
url: http://research.microsoft.com/pubs/67414/criminisi_pami2006.pdf
month: '09'
page: 1480 - 1492
publication: IEEE Transactions on Pattern Analysis and Machine Intelligence
publication_status: published
publisher: IEEE
publist_id: '3496'
quality_controlled: 0
status: public
title: Probabilistic fusion of stereo with color and contrast for bilayer segmentation
type: journal_article
volume: 28
year: '2006'
...