Ghent University Academic Bibliography

Advanced

Efficient foreground detection for real-time surveillance applications

Sebastian Grünwedel, Nemanja Petrovic UGent, Ljubomir Jovanov UGent, Jorge Niño Castañeda UGent, Aleksandra Pizurica UGent and Wilfried Philips UGent (2013) ELECTRONICS LETTERS. 49(18). p.1143-1144
abstract
The problem of foreground detection in real-time video surveillance applications is addressed. Proposes is a framework, which is computationally cheap and has low memory requirements. It combines two simple processing blocks, both of which are essentially background subtraction algorithms. The main novelty of the approach is a combination of an autoregressive moving average filter with two background models having different adaptation speeds. The first model, having a lower adaptation speed, models long-term background and detects foreground objects by finding areas in the current frame which significantly differ from the proposed background model. The second model, with a higher adaptation speed, models the short-term background and is responsible for finding regions in the scene with a high foreground object activity. The final foreground detection is built by combining the outputs from these building blocks. The foreground obtained by the long-term modelling block is verified by the output of the short-term modelling block, i.e. only the objects exhibiting significant motion are detected as real foreground objects. The proposed method results in a very good foreground detection performance at a low computational cost.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
computer vision, background subtraction, FG/BG segmentation
journal title
ELECTRONICS LETTERS
volume
49
issue
18
pages
1143 - 1144
Web of Science type
Article
Web of Science id
000323554400020
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
1.068 (2013)
JCR rank
141/248 (2013)
JCR quartile
3 (2013)
ISSN
0013-5194
DOI
10.1049/el.2013.1944
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
4106896
handle
http://hdl.handle.net/1854/LU-4106896
date created
2013-07-28 23:30:40
date last changed
2016-12-19 15:45:10
@article{4106896,
  abstract     = {The problem of foreground detection in real-time video surveillance applications is addressed. Proposes is a framework, which is computationally cheap and has low memory requirements. It combines two simple processing blocks, both of which are essentially background subtraction algorithms. The main novelty of the approach is a combination of an autoregressive moving average filter with two background models having different adaptation speeds. The first model, having a lower adaptation speed, models long-term background and detects foreground objects by finding areas in the current frame which significantly differ from the proposed background model. The second model, with a higher adaptation speed, models the short-term background and is responsible for finding regions in the scene with a high foreground object activity. The final foreground detection is built by combining the outputs from these building blocks. The foreground obtained by the long-term modelling block is verified by the output of the short-term modelling block, i.e. only the objects exhibiting significant motion are detected as real foreground objects. The proposed method results in a very good foreground detection performance at a low computational cost.},
  author       = {Gr{\"u}nwedel, Sebastian and Petrovic, Nemanja and Jovanov, Ljubomir and Ni{\~n}o Casta{\~n}eda, Jorge and Pizurica, Aleksandra and Philips, Wilfried},
  issn         = {0013-5194},
  journal      = {ELECTRONICS LETTERS},
  keyword      = {computer vision,background subtraction,FG/BG segmentation},
  language     = {eng},
  number       = {18},
  pages        = {1143--1144},
  title        = {Efficient foreground detection for real-time surveillance applications},
  url          = {http://dx.doi.org/10.1049/el.2013.1944},
  volume       = {49},
  year         = {2013},
}

Chicago
Grünwedel, Sebastian, Nemanja Petrovic, Ljubomir Jovanov, Jorge Niño Castañeda, Aleksandra Pizurica, and Wilfried Philips. 2013. “Efficient Foreground Detection for Real-time Surveillance Applications.” Electronics Letters 49 (18): 1143–1144.
APA
Grünwedel, S., Petrovic, N., Jovanov, L., Niño Castañeda, J., Pizurica, A., & Philips, W. (2013). Efficient foreground detection for real-time surveillance applications. ELECTRONICS LETTERS, 49(18), 1143–1144.
Vancouver
1.
Grünwedel S, Petrovic N, Jovanov L, Niño Castañeda J, Pizurica A, Philips W. Efficient foreground detection for real-time surveillance applications. ELECTRONICS LETTERS. 2013;49(18):1143–4.
MLA
Grünwedel, Sebastian, Nemanja Petrovic, Ljubomir Jovanov, et al. “Efficient Foreground Detection for Real-time Surveillance Applications.” ELECTRONICS LETTERS 49.18 (2013): 1143–1144. Print.