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    Optical flow estimation using the Fisher-Rao metric

    Maybank, Stephen and Ieng, S.-H. and Migliore, D. and Benosman, R. (2021) Optical flow estimation using the Fisher-Rao metric. Neuromorphic Computing and Engineering 1 (024004), ISSN 2634-4386.

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    Abstract

    The optical flow in an event camera is estimated using measurements in the Address Event Representation (AER). Each measurement consists of a pixel address and the time at which a change in the pixel value equalled a given fixed threshold. The measurements in a small region of the pixel array and within a given window in time are approximated by a probability distribution defined on a finite set. The distributions obtained in this way form a three dimensional family parameterized by the pixel addresses and by time. Each parameter value has an associated Fisher-Rao matrix obtained from the Fisher-Rao metric for the parameterized family of distributions. The optical flow vector at a given pixel and at a given time is obtained from the eigenvector of the associated Fisher-Rao matrix with the least eigenvalue. The Fisher-Rao algorithm for estimating optical flow is tested on eight datasets, of which six have ground truth optical flow. It is shown that the Fisher-Rao algorithm performs well in comparison with two state of the art algorithms for estimating optical flow from AER measurements.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): address event representation, AER, asynchronous image sensor, event camera, Fisher-Rao metric, Kullback-Leibler divergence, optical flow, OptiTrack motion capture
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Steve Maybank
    Date Deposited: 27 Jan 2022 14:12
    Last Modified: 29 Jan 2022 07:40
    URI: https://eprints.bbk.ac.uk/id/eprint/46118

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