By Topic

A Robust Moving Objects Detection Algorithm Based on Gaussian Mixture Model

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 $13
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

4 Author(s)
Song Xuehua ; Dept. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., Zhenjiang, China ; Chen Yu ; Geng Jianfeng ; Chen Jingzhu

The paper proposes a novel algorithm which can effectively resolve the problems of background disturbance and light changes in allusion to the problem that the background subtraction is sensitive to light changes. The algorithm, combined with the methods of background subtraction and adjacent frame difference, adopts Gaussian mixture model to avoid the impact of background disturbance. By using the idea of adjacent frame difference for reference, it deals with light changes by background reconstruction and constructing the function of dynamic learning efficiency. The algorithm is simulated under the circumstance of background disturbance and light changes, the experimental results show that the algorithm is more efficient and robust than traditional methods, and it can attain background model in the complex condition quickly. The algorithm is particularly suitable to the intelligent video surveillance with static cameras.

Published in:

Information Technology and Computer Science, 2009. ITCS 2009. International Conference on  (Volume:1 )

Date of Conference:

25-26 July 2009