By Topic

An Enhanced Background Estimation Algorithm for Vehicle Detection in Urban Traffic Scenes

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

4 Author(s)
Vargas, M. ; Dept. of Autom. & Syst. Eng., Univ. of Seville, Seville, Spain ; Milla, J.M. ; Toral, S.L. ; Barrero, F.

This paper proposes a new background subtraction algorithm based on the sigma-delta filter, which is intended to be used in urban traffic scenes. The original sigma-delta algorithm is a very interesting alternative due to its high computational efficiency. However, the background model quickly degrades in complex urban scenes because it is easily “contaminated” by slow-moving or temporarily stopped vehicles. Then, subsequent foreground validation steps are needed to refine the foreground detection mask. Instead of requiring any subsequent processing steps or resorting to algorithms with higher computational cost, the proposed algorithm tries to achieve a more stable background model by introducing a confidence measurement for each pixel. This confidence measurement assists in a selective background-model updating mechanism at the pixel level. Experimental comparative tests and a quantitative performance evaluation over typical urban traffic sequences corroborate the benefits of the proposed algorithm.

Published in:

Vehicular Technology, IEEE Transactions on  (Volume:59 ,  Issue: 8 )