A region-based approach to stereo matching for USAR

Brian McKinnon, Jacky Baltes, John Anderson

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

3 Citations (Scopus)

Abstract

Stereo vision for mobile robots is challenging, particularly when employing embedded systems with limited processing power. Objects in the field of vision must be extracted and represented in a fashion useful to the observer, while at the same time, methods must be in place for dealing with the large volume of data that stereo vision necessitates, in order that a practical frame rate may be obtained. We are working with stereo vision as the sole form of perception for Urban Search and Rescue (USAR) vehicles. This paper describes our procedure for extracting and matching object data using a stereo vision system. Initial results aro provided to demonstrate the potential of this system for USAR and other challenging domains.

Original languageEnglish
Title of host publicationRoboCup 2005
Subtitle of host publicationRobot Soccer World Cup IX
PublisherSpringer Verlag
Pages452-463
Number of pages12
ISBN (Print)9783540354376
Publication statusPublished - 2006 Jan 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4020 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fingerprint

Stereo Matching
Stereo vision
Stereo Vision
Vision System
Embedded systems
Mobile Robot
Embedded Systems
Mobile robots
Observer
Processing
Demonstrate
Object

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

McKinnon, B., Baltes, J., & Anderson, J. (2006). A region-based approach to stereo matching for USAR. In RoboCup 2005: Robot Soccer World Cup IX (pp. 452-463). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4020 LNAI). Springer Verlag.

A region-based approach to stereo matching for USAR. / McKinnon, Brian; Baltes, Jacky; Anderson, John.

RoboCup 2005: Robot Soccer World Cup IX. Springer Verlag, 2006. p. 452-463 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4020 LNAI).

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

McKinnon, B, Baltes, J & Anderson, J 2006, A region-based approach to stereo matching for USAR. in RoboCup 2005: Robot Soccer World Cup IX. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4020 LNAI, Springer Verlag, pp. 452-463.
McKinnon B, Baltes J, Anderson J. A region-based approach to stereo matching for USAR. In RoboCup 2005: Robot Soccer World Cup IX. Springer Verlag. 2006. p. 452-463. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
McKinnon, Brian ; Baltes, Jacky ; Anderson, John. / A region-based approach to stereo matching for USAR. RoboCup 2005: Robot Soccer World Cup IX. Springer Verlag, 2006. pp. 452-463 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{2c38df448d334ffea410797353b25ce1,
title = "A region-based approach to stereo matching for USAR",
abstract = "Stereo vision for mobile robots is challenging, particularly when employing embedded systems with limited processing power. Objects in the field of vision must be extracted and represented in a fashion useful to the observer, while at the same time, methods must be in place for dealing with the large volume of data that stereo vision necessitates, in order that a practical frame rate may be obtained. We are working with stereo vision as the sole form of perception for Urban Search and Rescue (USAR) vehicles. This paper describes our procedure for extracting and matching object data using a stereo vision system. Initial results aro provided to demonstrate the potential of this system for USAR and other challenging domains.",
author = "Brian McKinnon and Jacky Baltes and John Anderson",
year = "2006",
month = "1",
day = "1",
language = "English",
isbn = "9783540354376",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "452--463",
booktitle = "RoboCup 2005",

}

TY - GEN

T1 - A region-based approach to stereo matching for USAR

AU - McKinnon, Brian

AU - Baltes, Jacky

AU - Anderson, John

PY - 2006/1/1

Y1 - 2006/1/1

N2 - Stereo vision for mobile robots is challenging, particularly when employing embedded systems with limited processing power. Objects in the field of vision must be extracted and represented in a fashion useful to the observer, while at the same time, methods must be in place for dealing with the large volume of data that stereo vision necessitates, in order that a practical frame rate may be obtained. We are working with stereo vision as the sole form of perception for Urban Search and Rescue (USAR) vehicles. This paper describes our procedure for extracting and matching object data using a stereo vision system. Initial results aro provided to demonstrate the potential of this system for USAR and other challenging domains.

AB - Stereo vision for mobile robots is challenging, particularly when employing embedded systems with limited processing power. Objects in the field of vision must be extracted and represented in a fashion useful to the observer, while at the same time, methods must be in place for dealing with the large volume of data that stereo vision necessitates, in order that a practical frame rate may be obtained. We are working with stereo vision as the sole form of perception for Urban Search and Rescue (USAR) vehicles. This paper describes our procedure for extracting and matching object data using a stereo vision system. Initial results aro provided to demonstrate the potential of this system for USAR and other challenging domains.

UR - http://www.scopus.com/inward/record.url?scp=37249014055&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=37249014055&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:37249014055

SN - 9783540354376

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 452

EP - 463

BT - RoboCup 2005

PB - Springer Verlag

ER -