| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 532996 | Pattern Recognition | 2005 | 10 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Yang Wang, Tele Tan, Kia-Fock Loe, Jian-Kang Wu,