Particle filter in vision tracking
Cuevas, Erik V. ;  Zaldivar, Daniel ;  Rojas, Raúl ;  Universität <Berlin, Freie Universität> / Fachbereich Mathematik und Informatik

Main titleParticle filter in vision tracking
AuthorCuevas, Erik V.
AuthorZaldivar, Daniel
AuthorRojas, Raúl
InstitutionUniversität <Berlin, Freie Universität> / Fachbereich Mathematik und Informatik
No. of Pages11 S.
Series Freie Universität Berlin, Fachbereich Mathematik und Informatik : Ser. B, Informatik ; [20]05,13
Classification (DDC)004 Data processing and Computer science
AbstractThe extended Kalman filter (EKF) has been used as the standard
technique for performing recursive nonlinear estimation in vision tracking.
In this report, we present an alternative filter with performance superior to
that of the EKF. This algorithm, referred to as the Particle filter. Particle
filtering was originally developed to track objects in clutter (multi-modal
distribution). We present as results the filter behavior when exist objects
with similar characteristic to the object to track.
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FU DepartmentDepartment of Mathematics and Computer Science
Other affiliation(s)Institut für Informatik
Year of publication2005
Type of documentWorking paper
Terms of use/Rights Nutzungsbedingungen
Created at2009-06-23 : 09:53:07
Last changed2015-03-03 : 01:42:35
Static URLhttp://edocs.fu-berlin.de/docs/receive/FUDOCS_document_000000002402