Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Dynamic vergence using disparity flux

Full metadata record
DC Field Value Language
dc.contributor.authorKim, HJ-
dc.contributor.authorYoo, MH-
dc.contributor.authorLee, SW-
dc.date.accessioned2021-09-09T12:37:33Z-
dc.date.available2021-09-09T12:37:33Z-
dc.date.created2021-06-18-
dc.date.issued2000-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/124416-
dc.description.abstractVergence movement enables human and vertebrates, having stereo vision, to perceive the depth of an interesting visual target fixated by both left and right eyes. To simulate this on a binocular robotic camera head, we propose a new control model for vergence movement using disparity flux. Experimental results showed that this model is efficient in controlling vergence movement in various environments. When the perception-action cycle is short enough to approach to the real-time frame rate, the precision of disparity flux increases, and then a more accurate control of vergence movements on the stereo robotic head is possible.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleDynamic vergence using disparity flux-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, SW-
dc.identifier.wosid000166852800018-
dc.identifier.bibliographicCitationBIOLOGICALLY MOTIVATED COMPUTER VISION, PROCEEDING, v.1811, pp.179 - 188-
dc.relation.isPartOfBIOLOGICALLY MOTIVATED COMPUTER VISION, PROCEEDING-
dc.citation.titleBIOLOGICALLY MOTIVATED COMPUTER VISION, PROCEEDING-
dc.citation.volume1811-
dc.citation.startPage179-
dc.citation.endPage188-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Cybernetics-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Artificial Intelligence > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Seong Whan photo

Lee, Seong Whan
인공지능학과
Read more

Altmetrics

Total Views & Downloads

BROWSE