By Topic

Fast Background Subtraction and Shadow Elimination Using Improved 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
$31 $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

2 Author(s)
Zhen Tang ; Beijing Jiaotong Univ., Beijing ; Zhenjiang Miao

Background subtraction is widely used to detect moving object from static cameras. It is usually regard as one of the most important step in applications such as traffic monitoring, human motion capture and recognition, video surveillance, etc. In order to get a good performance of the whole system, the background subtraction method could not be so time and space consuming, and the accuracy is also required. Gaussian mixture model is a robust background subtraction method and is widely used ever since it is proposed. Some of the shortcomings of this model such as slow updating rate, slow initialization procedure and time and space consuming can be seen in some literatures and the corresponding resolution methods are also proposed. In this paper, an improved Gaussian mixture model is proposed to save time and space. New shadow detection and noise removing method are also proposed. the accuracy is also required.

Published in:

Haptic, Audio and Visual Environments and Games, 2007. HAVE 2007. IEEE International Workshop on

Date of Conference:

12-14 Oct. 2007