Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,083

The DOI matches its Crossref record.

Background subtraction techniques: a review

Piccardi, M.·2005·2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/icsmc.2004.1400815

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 2,083

Metadata

Authors
Piccardi, M.
Venue
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)
Publisher
IEEE
Published
2005-04-12
Pages
3099-3104
ISSN
1062-922X (ISSN-L)
OpenAlex
W2121274305
Cited by
2,083
References
0
FWCI
51.06
Type
conference paper
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Background subtraction techniques: a review. https://app.cochat.ai/papers/10.1109/icsmc.2004.1400815
The paper
Piccardi, M. (2005). Background subtraction techniques: a review. 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583). https://doi.org/10.1109/icsmc.2004.1400815

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.