DocumentCode :
3492650
Title :
Real-time background subtraction for video surveillance: From research to reality
Author :
Hedayati, M. ; Zaki, W. Mimi Diyana W. ; Hussain, Aini
Author_Institution :
Dept. of Electr., Electron. & Syst. Eng., Univ. Kebangsaan Malaysia, Bangi, Malaysia
fYear :
2010
fDate :
21-23 May 2010
Firstpage :
1
Lastpage :
6
Abstract :
This paper reviews and evaluates performance of few common background subtraction algorithms which are median-based, Gaussian-based and Kernel density-based approaches. These algorithms are tested using four sets of image sequences contributed by Wallflower datasets. They are the image sequences of different challenging environments that may reflect the real scenario in video surveillances. The performances of these approaches are evaluated in terms of processing speed, memory usage as well as object segmentation accuracy. The results demonstrate that Gaussian-based approach is the best approach for real-time applications, compromising between accuracy and computational time. Besides, this paper may provide a better understanding of algorithm behaviours implemented in different situation for real-time video surveillance applications.
Keywords :
image segmentation; image sequences; video surveillance; image sequences; object segmentation; real-time background subtraction; video surveillance; Change detection algorithms; Gaussian processes; Image sequences; Kernel; Layout; Object detection; Real time systems; Signal processing algorithms; Video signal processing; Video surveillance; Background Subtraction; Gaussian Mixture Modal; KDE; Median; Real-Time Video Surveillance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Its Applications (CSPA), 2010 6th International Colloquium on
Conference_Location :
Mallaca City
Print_ISBN :
978-1-4244-7121-8
Type :
conf
DOI :
10.1109/CSPA.2010.5545277
Filename :
5545277
Link To Document :
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