Motion parallax for object localization in electric fields.

electric field electrolocation electroreceptor field simulation motion parallax object localization weakly electric fish

Journal

Bioinspiration & biomimetics
ISSN: 1748-3190
Titre abrégé: Bioinspir Biomim
Pays: England
ID NLM: 101292902

Informations de publication

Date de publication:
22 12 2021
Historique:
received: 13 09 2021
accepted: 21 10 2021
pubmed: 22 10 2021
medline: 19 3 2022
entrez: 21 10 2021
Statut: epublish

Résumé

Parallax, as a visual effect, is used for depth perception of objects. But is there also the effect of parallax in the context of electric field imagery? In this work, the example of weakly electric fish is used to investigate how the self-generated electric field that these fish utilize for orientation and communication alike, may be used as a template to define electric parallax. The skin of the electric fish possesses a vast amount of electroreceptors that detect the self-emitted dipole-like electric field. In this work, the weakly electric fish is abstracted as an electric dipole with a sensor line in between the two emitters. With an analytical description of the object distortion for a uniform electric field, the distortion in a dipole-like field is simplified and simulated. On the basis of this simulation, the parallax effect could be demonstrated in electric field images i.e. by closer inspection of voltage profiles on the sensor line. Therefore, electric parallax can be defined as the relative movement of a signal feature of the voltage profile (here, the maximum or peak of the voltage profile) that travels along the sensor line peak trace (PT). The PT width correlates with the object's vertical distance to the sensor line, as close objects create a large PT and distant objects a small PT, comparable with the effect of visual motion parallax.

Identifiants

pubmed: 34673547
doi: 10.1088/1748-3190/ac3215
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2021 IOP Publishing Ltd.

Auteurs

Kevin Hunke (K)

Biomechatronics Group, Faculty of Engineering and Mathematics, University of Applied Sciences, Bielefeld, Germany.

Jacob Engelmann (J)

Active Sensing, Faculty of Biology, Bielefeld University, Bielefeld, Germany.

Hanno Gerd Meyer (HG)

Biomechatronics Group, Faculty of Engineering and Mathematics, University of Applied Sciences, Bielefeld, Germany.

Axel Schneider (A)

Biomechatronics Group, Faculty of Engineering and Mathematics, University of Applied Sciences, Bielefeld, Germany.

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Classifications MeSH