The probabilistic multi-hypothesis tracking (PMHT) algorithm is extended for application to classification. The PMHT model is reformulated as a bank of continuous-state hidden Markov models, allowing for supervised learning of the class-conditional probability density models, and for likelihood evaluation of multicomponent signals.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Multicomponent signal classification using the PMHT algorithm


    Beteiligte:
    Ainsleigh, P. (Autor:in) / Luginbuhl, T. (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    523525 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Multicomponent Signal Classification using the PMHT Algorithm

    Ainsleigh, P. / Luginbuhl, T. / International Society of Information Fusion et al. | British Library Conference Proceedings | 2002


    The Pedestrian PMHT

    Efe, M. / Willett, P. / International Society of Information Fusion et al. | British Library Conference Proceedings | 2002


    The pedestrian PMHT

    Efe, M. / Ruan, Y. / Willett, P. | IEEE | 2002


    PMHT with the True Association Probability

    Dunham, Darin T. | IEEE | 2007


    The turbo PMHT

    Yanhua Ruan / Willett, P. | IEEE | 2004