DocumentCode
548994
Title
Robust background subtraction on traffic videos
Author
Nunes, E. ; Conci, A. ; Sánchez, A.
Author_Institution
Inst. de Comput., Univ. Fed. Fluminense, Niterói, Brazil
fYear
2011
fDate
16-18 June 2011
Firstpage
1
Lastpage
4
Abstract
Background subtraction involves processing of a video sequence from a static camera to detect the foreground objects in all frames. This paper introduces a robust background subtraction technique, the Adaptive Local Threshold (ALT) algorithm, which it is based on the Approximate Median Filter (AMF). It has been applied to accurately extract the moving vehicles on complex weather traffic videos (i.e. fog and snow scenes). Experimental results have shown that the proposed algorithm produces similar qualitative detection results (based on the Jaccard coefficient) than AMF for the tested videos. Additionally, our method has the advantage of not needing any threshold parameter to detect the foreground targets.
Keywords
image sequences; median filters; object detection; traffic engineering computing; video signal processing; Jaccard coefficient; adaptive local threshold algorithm; approximate median filter; complex weather traffic videos; fog scenes; foreground object detection; moving vehicle extraction; robust background subtraction; snow scenes; static camera; video sequence; Adaptation models; Computational modeling; Meteorology; Pixel; Robustness; Vehicles; Videos; adaptive threshold; background subtraction; segmentation; video-based traffic analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signals and Image Processing (IWSSIP), 2011 18th International Conference on
Conference_Location
Sarajevo
ISSN
2157-8672
Print_ISBN
978-1-4577-0074-3
Type
conf
Filename
5977411
Link To Document