Neurofuzzy prediction for visual tracking
Cuevas, Erik V. ;  Zaldivar, Daniel ;  Rojas, Raúl ;  Universität <Berlin, Freie Universität> / Fachbereich Mathematik und Informatik

Main titleNeurofuzzy prediction for visual tracking
AuthorCuevas, Erik V.
AuthorZaldivar, Daniel
AuthorRojas, Raúl
InstitutionUniversität <Berlin, Freie Universität> / Fachbereich Mathematik und Informatik
No. of Pages18 S.
Series Freie Universität Berlin, Fachbereich Mathematik und Informatik : Ser. B, Informatik ; [20]03,16
Classification (DDC)004 Data processing and Computer science
AbstractReal 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.
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FU DepartmentDepartment of Mathematics and Computer Science
Other affiliation(s)Institut für Informatik
Year of publication2003
Type of documentWorking paper
Terms of use/Rights Nutzungsbedingungen
Created at2009-05-13 : 09:38:47
Last changed2015-03-03 : 01:40:32
Static URLhttp://edocs.fu-berlin.de/docs/receive/FUDOCS_document_000000001927