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|Title:||A probabilistic approach for foreground and shadow segmentation in monocular image sequences|
Markov random field
|Citation:||Wang, Y., Tan, T., Loe, K.-F., Wu, J.-K. (2005). A probabilistic approach for foreground and shadow segmentation in monocular image sequences. Pattern Recognition 38 (11) : 1937-1946. ScholarBank@NUS Repository. https://doi.org/10.1016/j.patcog.2005.02.006|
|Abstract:||This paper presents a novel method of foreground and shadow segmentation in monocular indoor image sequences. The models of background, edge information, and shadow are set up and adaptively updated. A Bayesian network is proposed to describe the relationships among the segmentation label, background, intensity, and edge information. A maximum a posteriori - Markov random field estimation is used to boost the spatial connectivity of segmented regions. © 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.|
|Source Title:||Pattern Recognition|
|Appears in Collections:||Staff Publications|
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