Paper Info
Title
An Enhanced Background Estimation Algorithm for Vehicle Detection in Urban Traffic Scenes
Abstract
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.
Year
DOI
Venue
2010
10.1109/TVT.2010.2058134
Vehicular Technology, IEEE Transactions
Keywords
Field
DocType
image enhancement,object detection,sigma-delta modulation,traffic engineering computing,background subtraction algorithm,foreground detection mask,image enhancement,sigma-delta filter,urban traffic scenes,vehicle detection,Background estimation,sigma-delta filter,urban environments,vehicle detection
Iterative reconstruction,Background subtraction,Object detection,Computer vision,Algorithm design,Computer science,Image processing,Algorithm,Foreground detection,Artificial intelligence,Pixel,Computational complexity theory
Journal
Volume
Issue
ISSN
59
8
0018-9545
Citations 
PageRank 
References 
25
0.90
31
Authors
4
Name
Order
Citations
PageRank
Vargas, M.1250.90
Milla, J.M.2250.90
Toral, S.L.3392.98
Federico Barrero4282.05