Practical background estimation for mosaic blending with patch-based Markov random fields

by: Dae-Woong Kim, Ki-Sang Hong

Pattern Recognition, Vol. 41, No. 7. (July 2008), pp. 2145-2155.

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Abstract

In this paper, we present a new background estimation algorithm which effectively represents both background and foreground. The problem is formulated with a labeling problem over a patch-based Markov random field (MRF) and solved with a graph-cuts algorithm. Our method is applied to the problem of mosaic blending considering the moving objects and exposure variations of rotating and zooming camera. Also, to reduce seams in the estimated boundaries, we propose a simple exposure correction algorithm using intensities near the estimated boundaries.

@article{citeulike:2649138, abstract = {In this paper, we present a new background estimation algorithm which effectively represents both background and foreground. The problem is formulated with a labeling problem over a patch-based Markov random field (MRF) and solved with a graph-cuts algorithm. Our method is applied to the problem of mosaic blending considering the moving objects and exposure variations of rotating and zooming camera. Also, to reduce seams in the estimated boundaries, we propose a simple exposure correction algorithm using intensities near the estimated boundaries.}, author = {Kim, Dae-Woong and Hong, Ki-Sang }, citeulike-article-id = {2649138}, doi = {10.1016/j.patcog.2008.01.015}, journal = {Pattern Recognition}, keywords = {background\_subtraction, video, video\_segmentation}, month = {July}, number = {7}, pages = {2145--2155}, posted-at = {2008-04-10 13:38:52}, priority = {2}, title = {Practical background estimation for mosaic blending with patch-based Markov random fields}, url = {http://dx.doi.org/10.1016/j.patcog.2008.01.015}, volume = {41}, year = {2008} }

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TY - JOUR ID - citeulike:2649138 L3 - citeulike-article-id:2649138 TI - Practical background estimation for mosaic blending with patch-based Markov random fields JF - Pattern Recognition VL - 41 IS - 7 SP - 2145 EP - 2155 N2 - In this paper, we present a new background estimation algorithm which effectively represents both background and foreground. The problem is formulated with a labeling problem over a patch-based Markov random field (MRF) and solved with a graph-cuts algorithm. Our method is applied to the problem of mosaic blending considering the moving objects and exposure variations of rotating and zooming camera. Also, to reduce seams in the estimated boundaries, we propose a simple exposure correction algorithm using intensities near the estimated boundaries. KW - background_subtraction KW - video KW - video_segmentation AU - Kim, Dae-Woong AU - Hong, Ki-Sang PY - 2008/07// UR - http://dx.doi.org/10.1016/j.patcog.2008.01.015 ER -

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