--- _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' ...