A system capable of performing robust live ego-motion estimation for perspective cameras is presented. The system is powered by random sample consensus with preemptive scoring of the motion hypotheses. A general statement of the problem of efficient preemptive scoring is given. Then a theoretical investigation of preemptive scoring under a simple inlier-outlier model is performed. A practical preemption scheme is proposed and it is shown that the preemption is powerful enough to enable robust live structure and motion estimation.


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    Title :

    Preemptive RANSAC for live structure and motion estimation


    Contributors:
    Nister, (author)


    Publication date :

    2003-01-01


    Size :

    652758 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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