dc.contributor.author
Cuevas, Erik V.
dc.contributor.author
Zaldivar, Daniel
dc.contributor.author
Rojas, Raúl
dc.date.accessioned
2018-06-08T08:01:41Z
dc.date.available
2009-05-13T09:38:47.089Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/19199
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-22863
dc.description.abstract
Real time visual tracking is a complicated problem due the different dynamic
of the objects involved in the process. On one hand the algorithms for image
processing usually consume a lot of time on the other hand the motors and
mechanisms used for the camera movements are significantly slow. This work
describes the use of ANFIS model to reduce the delay’s effects in the control
for visual tracking and also explains how we resolved this problem by
predicting the target movement using a neurofuzzy approach.
de
dc.relation.ispartofseries
urn:nbn:de:kobv:188-fudocsseries000000000021-2
dc.rights.uri
http://www.fu-berlin.de/sites/refubium/rechtliches/Nutzungsbedingungen
dc.subject.ddc
000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, Systeme::004 Datenverarbeitung; Informatik
dc.title
Neurofuzzy prediction for visual tracking
refubium.affiliation
Mathematik und Informatik
de
refubium.affiliation.other
Institut für Informatik
refubium.mycore.fudocsId
FUDOCS_document_000000001927
refubium.resourceType.isindependentpub
no
refubium.series.name
Freie Universität Berlin, Fachbereich Mathematik und Informatik
refubium.series.reportNumber
03-16
refubium.mycore.derivateId
FUDOCS_derivate_000000000396
dcterms.accessRights.openaire
open access
