Adaptive Bayesian networks for video processing
File(s)
Published version
Author(s)
Lo,B.P.L.
Thiemjarus,S.
Yang,G.Z.
Type
Conference Paper
Abstract
Due to its static nature, the inference capability of Bayesian networks (BNs) often deteriorates when the basis of input data varies, especially in video processing applications where the environment often changes constantly. This paper presents an adaptive BN where the network parameters are adjusted in accordance to input variations. An efficient retraining method is introduced for updating the parameters and the proposed network is applied to shadow removal in video sequence processing with quantitative results demonstrating the significance of adapting the network with environmental changes.
Date Issued
2003
Citation
2003, pp.889-892
ISBN
9780780377509
0-7803-7750-8
ISSN
1522-4880
Publisher
IEEE
Source Title
IEEE International Conference on Image Processing
Conference
2003 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL 1, PROCEEDINGS
Start Page
889
End Page
892
Copyright Statement
© 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Source
IEEE international conference on image processing, Barcelona, Spain, 2003
Source Place
BARCELONA, SPAIN
Place of Publication
New York
Start Date
2003-09
Finish Date
2003-09
Coverage Spatial
Barcelona, Spain