By Topic

A fast algorithm for moving objects detection based on model switching

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

5 Author(s)
Chunhui Zhao ; College of Automation, Northwestern Polytechnical University, Xi¿an 710072, China ; Wei Liu ; Yi Wang ; Yongmei Cheng
more authors

A new method is proposed to improve background modeling speed. First, the pixels in current frame are classified into two classes according to average background to reduce the computing load. Second, different models for instance kernel or GMM based algorithm are used necessarily to deal with 'dead lock' of scene. Third, a kernel density estimation based on neighbor correlation is used to decrease the false positives'. Last, the two algorithm detection results are fused to detect moving object by the label of pixel. In this paper, a novel description of correlation about the pixel with its around pixels and a strategy of background modeling are proposed. Experimental results of outdoor complex scene demonstrate that the new algorithm is robustness to noise and good for real-time moving object detection.

Published in:

Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on

Date of Conference:

7-9 July 2008