Estimation of epipolar geometry can be done automatically in on-board stereovision systems, using interest points that are detected and matched. However, image disturbance that can happen in real-life situations can considerably lower the performance. A reliability score computing method is proposed, based on a fuzzy logic classifier. Its input is the data extracted from the estimation process. The classifier is trained with artificial image disturbance, using a set of typical image pairs. Results show that the computed score is indeed related to the performance of estimation.


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    Title :

    A fuzzy-logic classifier for estimating the reliability of the self calibration of an embedded stereovision system


    Contributors:


    Publication date :

    2008-10-01


    Size :

    677882 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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