Title
Reliable moving vehicle detection based on the filtering of swinging tree leaves and raindrops
Abstract
An efficient method for detecting moving vehicles based on the filtering of swinging trees and raindrops is proposed. To extract moving objects from the background, an adaptive background subtraction scheme with a shadow elimination model is used. Swinging trees are removed from foreground objects to reduce the computational complexity of subsequent tracking. Raindrops are removed from foreground objects when necessary. Performance evaluations are carried out using seven real-world traffic image sequences. Experimental results show average recognition rates of 96.83% and 97.20% for swinging trees and raindrops, respectively, indicating the feasibility of the proposed method.
Year
DOI
Venue
2012
10.1016/j.jvcir.2012.03.002
J. Visual Communication and Image Representation
Keywords
Field
DocType
vehicle detection,average recognition rate,real-world traffic image sequence,swinging tree leave,adaptive background subtraction scheme,efficient method,foreground object,performance evaluation,swinging tree,computational complexity,motion compensation,background subtraction,motion estimation
Background subtraction,Computer vision,Shadow,Motion detection,Pattern recognition,Motion compensation,Filter (signal processing),Artificial intelligence,Motion estimation,Drop (liquid),Mathematics,Computational complexity theory
Journal
Volume
Issue
ISSN
23
4
1047-3203
Citations 
PageRank 
References 
5
0.48
16
Authors
4
Name
Order
Citations
PageRank
Deng-Yuan Huang116315.28
Chen Chao-Ho23410.14
Wu-Chih Hu324427.01
Sing-Syong Su450.48