A stereo matching using variable windows and dynamic programming

Won P. Dong, Yun Seok Lee, Chang-Sung Jeong

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

1 Citation (Scopus)

Abstract

In this paper, we present a segment-based stereo matching algorithm using adaptive variable windows and dynamic programming with a robust disparity. We solve the problem of window shape and size using adaptive line masks and adaptive rectangular windows which are constrained by segments and visibility that reduces ambiguity produced by the occlusion in the computation window. In dynamic programming, we also propose the method that selects an efficient occlusion penalty.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages1277-1280
Number of pages4
Volume3809 LNAI
DOIs
Publication statusPublished - 2005 Dec 1
Event18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia
Duration: 2005 Dec 52005 Dec 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3809 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
CountryAustralia
CitySydney
Period05/12/505/12/9

Fingerprint

Stereo Matching
Masks
Dynamic programming
Dynamic Programming
Adaptive algorithms
Occlusion
Visibility
Matching Algorithm
Mask
Penalty
Line

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Dong, W. P., Lee, Y. S., & Jeong, C-S. (2005). A stereo matching using variable windows and dynamic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3809 LNAI, pp. 1277-1280). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI). https://doi.org/10.1007/11589990_186

A stereo matching using variable windows and dynamic programming. / Dong, Won P.; Lee, Yun Seok; Jeong, Chang-Sung.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3809 LNAI 2005. p. 1277-1280 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI).

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

Dong, WP, Lee, YS & Jeong, C-S 2005, A stereo matching using variable windows and dynamic programming. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3809 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3809 LNAI, pp. 1277-1280, 18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence, Sydney, Australia, 05/12/5. https://doi.org/10.1007/11589990_186
Dong WP, Lee YS, Jeong C-S. A stereo matching using variable windows and dynamic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3809 LNAI. 2005. p. 1277-1280. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11589990_186
Dong, Won P. ; Lee, Yun Seok ; Jeong, Chang-Sung. / A stereo matching using variable windows and dynamic programming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3809 LNAI 2005. pp. 1277-1280 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{ad021ba0bb2a460b94e9a201150e9d65,
title = "A stereo matching using variable windows and dynamic programming",
abstract = "In this paper, we present a segment-based stereo matching algorithm using adaptive variable windows and dynamic programming with a robust disparity. We solve the problem of window shape and size using adaptive line masks and adaptive rectangular windows which are constrained by segments and visibility that reduces ambiguity produced by the occlusion in the computation window. In dynamic programming, we also propose the method that selects an efficient occlusion penalty.",
author = "Dong, {Won P.} and Lee, {Yun Seok} and Chang-Sung Jeong",
year = "2005",
month = "12",
day = "1",
doi = "10.1007/11589990_186",
language = "English",
isbn = "3540304622",
volume = "3809 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "1277--1280",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - A stereo matching using variable windows and dynamic programming

AU - Dong, Won P.

AU - Lee, Yun Seok

AU - Jeong, Chang-Sung

PY - 2005/12/1

Y1 - 2005/12/1

N2 - In this paper, we present a segment-based stereo matching algorithm using adaptive variable windows and dynamic programming with a robust disparity. We solve the problem of window shape and size using adaptive line masks and adaptive rectangular windows which are constrained by segments and visibility that reduces ambiguity produced by the occlusion in the computation window. In dynamic programming, we also propose the method that selects an efficient occlusion penalty.

AB - In this paper, we present a segment-based stereo matching algorithm using adaptive variable windows and dynamic programming with a robust disparity. We solve the problem of window shape and size using adaptive line masks and adaptive rectangular windows which are constrained by segments and visibility that reduces ambiguity produced by the occlusion in the computation window. In dynamic programming, we also propose the method that selects an efficient occlusion penalty.

UR - http://www.scopus.com/inward/record.url?scp=33745584664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33745584664&partnerID=8YFLogxK

U2 - 10.1007/11589990_186

DO - 10.1007/11589990_186

M3 - Conference contribution

AN - SCOPUS:33745584664

SN - 3540304622

SN - 9783540304623

VL - 3809 LNAI

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

SP - 1277

EP - 1280

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

ER -