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
1Topics & keywords
Topics
Keywords
- Computer science
- Background subtraction
- Parametric statistics
- Artificial intelligence
- Machine learning
- Pixel
- Mathematics
- Statistics
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