Please use this identifier to cite or link to this item: https://doi.org/10.1111/1539-6924.00371
Title: A probabilistic method for foreground and shadow segmentation
Authors: Wang, Y.
Tan, T.
Loe, K.-F. 
Issue Date: 2003
Source: Wang, Y., Tan, T., Loe, K.-F. (2003). A probabilistic method for foreground and shadow segmentation. IEEE International Conference on Image Processing 3 : 937-940. ScholarBank@NUS Repository. https://doi.org/10.1111/1539-6924.00371
Abstract: This paper presents a probabilistic method for foreground segmentation that distinguishes moving objects from their cast shadows in monocular indoor image sequences. The models of background, shadow, and edge information are set up and adaptively updated. A Bayesian framework is proposed to describe the relationships among the segmentation label, background, intensity, and edge information. A Markov random field is used to boost the spatial connectivity of the segmented regions. The solution is obtained by maximizing the posterior probability density of the segmentation field.
Source Title: IEEE International Conference on Image Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/40824
DOI: 10.1111/1539-6924.00371
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