By Topic

Foreground segmentation for dynamic scenes with sudden illumination changes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
J. Li ; Beijing Jiaotong University, People¿s Republic of China ; Z. Miao

Foreground segmentation is a very difficult task in dynamic background, which is common in real-world environments, caused by for example waving foliage, rippling water or illumination changes owing to light switching etc. A large number of methods for foreground segmentation in dynamic background have been proposed in the past decades, but most of them can only handle repetitive movements or gradual changes in background, and fail when sudden illumination changes occur. This study proposes a new method, which can deal with both repetitive movements and gradual/sudden illumination changes. The authors use a two-layer Gaussian mixture model to represent the background under different lighting conditions and formulate a joint posterior function of background state and segmentation based on the learned model. Given a new image, the background state and foreground segmentation are simultaneously optimised in a Bayesian perspective using a nested two-layer optimisation. The authors test their method on several image sequences and compare the results qualitatively and quantitatively with some state-of-the-art methods to demonstrate the effectiveness of the method.

Published in:

IET Image Processing  (Volume:6 ,  Issue: 5 )