TY - JOUR TI - CompoundRay, an open-source tool for high-speed and high-fidelity rendering of compound eyes AU - Millward, Blayze AU - Maddock, Steve AU - Mangan, Michael A2 - Cardona, Albert A2 - Moore, Tirin A2 - Saalfeld, Stephan A2 - Straw, Andrew D VL - 11 PY - 2022 DA - 2022/10/13 SP - e73893 C1 - eLife 2022;11:e73893 DO - 10.7554/eLife.73893 UR - https://doi.org/10.7554/eLife.73893 AB - 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). KW - compound eyes KW - arthropod KW - compound vision KW - software KW - ray tracing KW - visual perspective JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -