In most multiple hypothesis tracking (MHT) implementations, the data association is solved using Murty's algorithm. However, since Murty's algorithm has no control over the diversity of measurement-to-track associations, often, the top associations vary only slightly. To overcome this problem and to provide more flexibility in the selection of hypotheses, a modified Murty's algorithm, which can achieve any user-defined (or adaptable) diversity of association of different types of tracks, is proposed.


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    Title :

    Modified Murty's Algorithm for Diverse Multitarget Top Hypothesis Extraction


    Contributors:


    Publication date :

    2013-01-01


    Size :

    1104764 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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