A collision prediction system for traffic intersections

Stefan Atev, Osama Masoud, Ravi Janardan, Nikolaos P Papanikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

Monitoring traffic intersections in real-time and predicting possible collisions is an important first step towards building an early collision warning system. We present the general vision methods used in a system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. A novel method for three-dimensional vehicle size estimation is presented. We also describe a method for target localization in real-world coordinates which allows for sequential incorporation of measurements from multiple cameras into a single target's state vector. Additionally, a fast implementation of a false-positive reduction method for the foreground pixel masks is developed. Finally, a low-overhead collision prediction algorithm using the time-as-axis paradigm is presented. The proposed system was able to perform in real-time on videos of quarter-VGA (320×240) resolution. The errors in target position and dimension estimates in a test video sequence are quantified.

Original languageEnglish (US)
Title of host publication2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Pages2844-2849
Number of pages6
DOIs
StatePublished - Dec 1 2005
EventIEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005 - Edmonton, AB, Canada
Duration: Aug 2 2005Aug 6 2005

Publication series

Name2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

Other

OtherIEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005
CountryCanada
CityEdmonton, AB
Period8/2/058/6/05

Fingerprint

Alarm systems
Masks
Pixels
Cameras
Monitoring

Keywords

  • Collision prediction
  • Machine vision
  • Real-time systems
  • Tracking
  • Traffic control (transportation)

Cite this

Atev, S., Masoud, O., Janardan, R., & Papanikolopoulos, N. P. (2005). A collision prediction system for traffic intersections. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS (pp. 2844-2849). [1545407] (2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS). https://doi.org/10.1109/IROS.2005.1545407

A collision prediction system for traffic intersections. / Atev, Stefan; Masoud, Osama; Janardan, Ravi; Papanikolopoulos, Nikolaos P.

2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS. 2005. p. 2844-2849 1545407 (2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Atev, S, Masoud, O, Janardan, R & Papanikolopoulos, NP 2005, A collision prediction system for traffic intersections. in 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS., 1545407, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 2844-2849, IEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005, Edmonton, AB, Canada, 8/2/05. https://doi.org/10.1109/IROS.2005.1545407
Atev S, Masoud O, Janardan R, Papanikolopoulos NP. A collision prediction system for traffic intersections. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS. 2005. p. 2844-2849. 1545407. (2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS). https://doi.org/10.1109/IROS.2005.1545407
Atev, Stefan ; Masoud, Osama ; Janardan, Ravi ; Papanikolopoulos, Nikolaos P. / A collision prediction system for traffic intersections. 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS. 2005. pp. 2844-2849 (2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS).
@inproceedings{19da5c3b3e8340039ad4ab8d05c4bb83,
title = "A collision prediction system for traffic intersections",
abstract = "Monitoring traffic intersections in real-time and predicting possible collisions is an important first step towards building an early collision warning system. We present the general vision methods used in a system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. A novel method for three-dimensional vehicle size estimation is presented. We also describe a method for target localization in real-world coordinates which allows for sequential incorporation of measurements from multiple cameras into a single target's state vector. Additionally, a fast implementation of a false-positive reduction method for the foreground pixel masks is developed. Finally, a low-overhead collision prediction algorithm using the time-as-axis paradigm is presented. The proposed system was able to perform in real-time on videos of quarter-VGA (320×240) resolution. The errors in target position and dimension estimates in a test video sequence are quantified.",
keywords = "Collision prediction, Machine vision, Real-time systems, Tracking, Traffic control (transportation)",
author = "Stefan Atev and Osama Masoud and Ravi Janardan and Papanikolopoulos, {Nikolaos P}",
year = "2005",
month = "12",
day = "1",
doi = "10.1109/IROS.2005.1545407",
language = "English (US)",
isbn = "0780389123",
series = "2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS",
pages = "2844--2849",
booktitle = "2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS",

}

TY - GEN

T1 - A collision prediction system for traffic intersections

AU - Atev, Stefan

AU - Masoud, Osama

AU - Janardan, Ravi

AU - Papanikolopoulos, Nikolaos P

PY - 2005/12/1

Y1 - 2005/12/1

N2 - Monitoring traffic intersections in real-time and predicting possible collisions is an important first step towards building an early collision warning system. We present the general vision methods used in a system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. A novel method for three-dimensional vehicle size estimation is presented. We also describe a method for target localization in real-world coordinates which allows for sequential incorporation of measurements from multiple cameras into a single target's state vector. Additionally, a fast implementation of a false-positive reduction method for the foreground pixel masks is developed. Finally, a low-overhead collision prediction algorithm using the time-as-axis paradigm is presented. The proposed system was able to perform in real-time on videos of quarter-VGA (320×240) resolution. The errors in target position and dimension estimates in a test video sequence are quantified.

AB - Monitoring traffic intersections in real-time and predicting possible collisions is an important first step towards building an early collision warning system. We present the general vision methods used in a system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. A novel method for three-dimensional vehicle size estimation is presented. We also describe a method for target localization in real-world coordinates which allows for sequential incorporation of measurements from multiple cameras into a single target's state vector. Additionally, a fast implementation of a false-positive reduction method for the foreground pixel masks is developed. Finally, a low-overhead collision prediction algorithm using the time-as-axis paradigm is presented. The proposed system was able to perform in real-time on videos of quarter-VGA (320×240) resolution. The errors in target position and dimension estimates in a test video sequence are quantified.

KW - Collision prediction

KW - Machine vision

KW - Real-time systems

KW - Tracking

KW - Traffic control (transportation)

UR - http://www.scopus.com/inward/record.url?scp=79957976712&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79957976712&partnerID=8YFLogxK

U2 - 10.1109/IROS.2005.1545407

DO - 10.1109/IROS.2005.1545407

M3 - Conference contribution

SN - 0780389123

SN - 9780780389120

T3 - 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

SP - 2844

EP - 2849

BT - 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

ER -