A confidence framework for the assessment of optical flow performance

Patricia Márquez-Valle

    Research output: Contribution to journalArticleResearchpeer-review

    Abstract

    Optical Flow (OF) is the input of a wide range of decision support systems such as car driver assistance, UAV guiding or medical diagnose. In these real situations, the absence of ground truth forces to assess OF quality using quantities computed from either sequences or the computed optical flow itself. These quantities are generally known as Confidence Measures, CM. Even if we have a proper confidence measure we still need a way to evaluate its ability to discard pixels with an OF prone to have a large error. Current approaches only provide a descriptive evaluation of the CM performance but such approaches are not capable to fairly compare different confidence measures and optical flow algorithms. Thus, it is of prime importance to define a framework and a general road map for the evaluation of optical flow performance.
    Original languageEnglish
    Pages (from-to)4-6
    JournalElectronic Letters on Computer Vision and Image Analysis
    Volume15
    Issue number2
    DOIs
    Publication statusPublished - 1 Jan 2016

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