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: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Steve Maybank |
| Date Deposited: | 27 Jan 2022 14:12 |
| Last Modified: | 09 Aug 2023 12:51 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/46118 |
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