A novel algorithm was developed to estimate scene depth by uniquely exploiting plenoptic image data. Plenoptic images allow multiple perspectives to be extracted from a single exposure from a single lens. Depth from disparity was calculated for every available perspective view using normalized cross correlation. This resulted in a large number of unique disparity maps, which were then combined in a least-squares sense, weighted by confidence coefficients to account for measurement uncertainty. The averaged disparity map was then transformed into a depth map using geometric optics. The accuracy of the algorithm was tested with a plenoptic camera on a small static target imaged throughout the depth of field. Depth was recovered with a standard deviation less than 5 mm, validating the algorithm.


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    Titel :

    Correlation-Based Depth Estimation with a Plenoptic Camera



    Erschienen in:

    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch


    Schlagwörter :

    Klassifikation :

    BKL:    55.50 Luftfahrzeugtechnik / 55.60 Raumfahrttechnik / 55.60 / 50.93 / 55.50 / 50.93 Weltraumforschung
    Lokalklassifikation TIB:    770/7040



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