Within the target tracking community there is strong interest in computing a ranked set of assignments of measurements to targets. These k-best assignments are then used to determine good approximations to the data association problem. Much earlier work described algorithms which either had exponential worst case time or were not guaranteed to return the k-best assignments. Danchick and Newnam (1993) described a fast algorithm for finding the exact k-best hypotheses. However, in the worst case, k! linear assignment problems must be solved. This correspondence describes an algorithm originally due to Murty (1968) for optimally determining a ranked set of assignments in polynomial time and which is linear in k.<>


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    On finding ranked assignments with application to multitarget tracking and motion correspondence


    Contributors:
    Cox, I.J. (author) / Miller, M.L. (author)


    Publication date :

    1995-01-01


    Size :

    601859 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English