dc.contributor.author
Cuevas, Erik V.
dc.contributor.author
Zaldivar, Daniel
dc.contributor.author
Rojas, Raúl
dc.date.accessioned
2018-06-08T08:00:55Z
dc.date.available
2009-06-23T09:40:09.832Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/19186
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-22852
dc.description.abstract
The Kalman filter has been used successfully in different prediction
applications or state determination of a system. One important field in
computer vision is the object tracking. Different movement conditions and
occlusions can hinder the vision tracking of an object. In this report we
present the use of the Kalman filter in the vision tracking. We consider the
capacity of the Kalman filter to allow small occlusions and also the use of
the extended Kalman filter (EKF) to model complex movements of objects.
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
Kalman filter for vision tracking
refubium.affiliation
Mathematik und Informatik
de
refubium.affiliation.other
Institut für Informatik
refubium.mycore.fudocsId
FUDOCS_document_000000002397
refubium.resourceType.isindependentpub
no
refubium.series.name
Freie Universität Berlin, Fachbereich Mathematik und Informatik
refubium.series.reportNumber
05-12
refubium.mycore.derivateId
FUDOCS_derivate_000000000473
dcterms.accessRights.openaire
open access
