reviewApr 12, 2005Closed access

Background subtraction techniques: a review

The University of Sydney · University of Technology Sydney

Indexed incrossref

Abstract

Background subtraction is a widely used approach for detecting moving objects from static cameras. Many different methods have been proposed over the recent years and both the novice and the expert can be confused about their benefits and limitations. In order to overcome this problem, this paper provides a review of the main methods and an original categorisation based on speed, memory requirements and accuracy. Such a review can effectively guide the designer to select the most suitable method for a given application in a principled way. Methods reviewed include parametric and non-parametric background density estimates and spatial correlation approaches.

Citation impact

2,094
total citations
FWCI
58.61
Percentile
100%
References
15
Citations per year

Authors

1

Topics & keywords

Keywords
  • Computer science
  • Background subtraction
  • Parametric statistics
  • Artificial intelligence
  • Machine learning
  • Pixel
  • Mathematics
  • Statistics
No related works found for this paper.