Median model for background subtraction in intelligent transportation system

Peijun Shi, Elizabeth G. Jones, Qiuming Zhu

Research output: Contribution to journalConference article

7 Citations (Scopus)

Abstract

A median model and an improved median model were proposed for background image generation and vehicle detection. The median model has an impressive performance in handling slow moving or even stationary vehicles. A mask-classified updating method was introduced to update the background image in the short-term, where only classified background pixels are being used for updating. The combination of the improved median model and mask-classified updating has several advantages such as it handles slow moving or even stationary vehicles and it can be used in real time image processing.

Original languageEnglish (US)
Pages (from-to)168-176
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5298
DOIs
StatePublished - Dec 1 2004
EventImaging Processing: Algorithms and Systems III - San Jose, CA, United States
Duration: Jan 19 2004Jan 20 2004

Fingerprint

Intelligent Transportation Systems
Background Subtraction
subtraction
Updating
vehicles
Mask
Masks
Real-time Image Processing
masks
Vehicle Detection
Model
image processing
Image processing
Pixel
Update
Pixels
pixels
Background

Keywords

  • Background subtraction
  • Object classification
  • Vehicle detection
  • Vehicle tracking

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Median model for background subtraction in intelligent transportation system. / Shi, Peijun; Jones, Elizabeth G.; Zhu, Qiuming.

In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 5298, 01.12.2004, p. 168-176.

Research output: Contribution to journalConference article

@article{f3d823b359df47d69e50964ca92758da,
title = "Median model for background subtraction in intelligent transportation system",
abstract = "A median model and an improved median model were proposed for background image generation and vehicle detection. The median model has an impressive performance in handling slow moving or even stationary vehicles. A mask-classified updating method was introduced to update the background image in the short-term, where only classified background pixels are being used for updating. The combination of the improved median model and mask-classified updating has several advantages such as it handles slow moving or even stationary vehicles and it can be used in real time image processing.",
keywords = "Background subtraction, Object classification, Vehicle detection, Vehicle tracking",
author = "Peijun Shi and Jones, {Elizabeth G.} and Qiuming Zhu",
year = "2004",
month = "12",
day = "1",
doi = "10.1117/12.525553",
language = "English (US)",
volume = "5298",
pages = "168--176",
journal = "Proceedings of SPIE - The International Society for Optical Engineering",
issn = "0277-786X",
publisher = "SPIE",

}

TY - JOUR

T1 - Median model for background subtraction in intelligent transportation system

AU - Shi, Peijun

AU - Jones, Elizabeth G.

AU - Zhu, Qiuming

PY - 2004/12/1

Y1 - 2004/12/1

N2 - A median model and an improved median model were proposed for background image generation and vehicle detection. The median model has an impressive performance in handling slow moving or even stationary vehicles. A mask-classified updating method was introduced to update the background image in the short-term, where only classified background pixels are being used for updating. The combination of the improved median model and mask-classified updating has several advantages such as it handles slow moving or even stationary vehicles and it can be used in real time image processing.

AB - A median model and an improved median model were proposed for background image generation and vehicle detection. The median model has an impressive performance in handling slow moving or even stationary vehicles. A mask-classified updating method was introduced to update the background image in the short-term, where only classified background pixels are being used for updating. The combination of the improved median model and mask-classified updating has several advantages such as it handles slow moving or even stationary vehicles and it can be used in real time image processing.

KW - Background subtraction

KW - Object classification

KW - Vehicle detection

KW - Vehicle tracking

UR - http://www.scopus.com/inward/record.url?scp=8844228895&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=8844228895&partnerID=8YFLogxK

U2 - 10.1117/12.525553

DO - 10.1117/12.525553

M3 - Conference article

AN - SCOPUS:8844228895

VL - 5298

SP - 168

EP - 176

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

SN - 0277-786X

ER -