Millward, B., Maddock, S. orcid.org/0000-0003-3179-0263 and Mangan, M. orcid.org/0000-0002-0293-8874 (2022) CompoundRay, an open-source tool for high-speed and high-fidelity rendering of compound eyes. eLife, 11. e73893. ISSN 2050-084X
Abstract
Revealing the functioning of compound eyes is of interest to biologists and engineers alike who wish to understand how visually complex behaviours (e.g. detection, tracking, and navigation) arise in nature, and to abstract concepts to develop novel artificial sensory systems. A key investigative method is to replicate the sensory apparatus using artificial systems, allowing for investigation of the visual information that drives animal behaviour when exposed to environmental cues. To date, ‘compound eye models’ (CEMs) have largely explored features such as field of view and angular resolution, but the role of shape and overall structure have been largely overlooked due to modelling complexity. Modern real-time ray-tracing technologies are enabling the construction of a new generation of computationally fast, high-fidelity CEMs. This work introduces a new open-source CEM software (CompoundRay) that is capable of accurately rendering the visual perspective of bees (6000 individual ommatidia arranged on 2 realistic eye surfaces) at over 3000 frames per second. We show how the speed and accuracy facilitated by this software can be used to investigate pressing research questions (e.g. how low resolution compound eyes can localise small objects) using modern methods (e.g. machine learning-based information exploration).
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Millward et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Tools and Resources; Computational and Systems Biology; Neuroscience; compound eyes; arthropod; compound vision; software; ray tracing; visual perspective |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/P006094/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/S030964/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Nov 2022 11:05 |
Last Modified: | 21 Nov 2022 16:40 |
Status: | Published |
Publisher: | eLife Sciences Publications Ltd |
Refereed: | Yes |
Identification Number: | 10.7554/elife.73893 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:192806 |