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    Comparing a Kalman Filter and a Particle Filter in a Multiple Objects Tracking Application

    TítuloComparing a Kalman Filter and a Particle Filter in a Multiple Objects Tracking Application
    Tipo de publicaciónConference Paper
    Año de publicación2007
    AutoresMarron, M, Garcia, JC, Sotelo, MA, Cabello-Aguilar, M, Pizarro, D, Huerta, F, Cerro, J
    Idioma de publicaciónEnglish
    Conference Name2007 IEEE International Symposium on Intelligent Signal Processing
    Páginas1-6
    EditorialIEEE
    Conference LocationAlcalá de Henares, Spain
    Fecha de publicación10/2007
    Numero ISBN978-1-4244-0829-0
    Palabras claveMulti-Object Tracking, position estimation, Probabilistic Algorithms, robotics
    DOI10.1109/WISP.2007.4447520
    URLhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?asf_arn=null&asf_iid=null&asf_pun=4447489&asf_in=null&asf_rpp=null&asf_iv=null&asf_sp=null&asf_pn=3
    Resumen

    Two of the most important solutions in position estimation are compared, in this paper, in order to test their efficiency in a multi-tracking application in an unstructured and complex environment. A Particle Filter is extended and adapted with a clustering process in order to track a variable number of objects. The other approach is to use a Kalman Filter with an association algorithm for each of the objects to track. Both algorithms are described in the paper and the results obtained with their real-time execution in the mentioned application are shown. Finally interesting conclusions extracted from this comparison are remarked at the end.

    Resumen

    Two of the most important solutions in position estimation are compared, in this paper, in order to test their efficiency in a multi-tracking application in an unstructured and complex environment. A Particle Filter is extended and adapted with a clustering process in order to track a variable number of objects. The other approach is to use a Kalman Filter with an association algorithm for each of the objects to track. Both algorithms are described in the paper and the results obtained with their real-time execution in the mentioned application are shown. Finally interesting conclusions extracted from this comparison are remarked at the end.

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