title: How do field of view and resolution affect the information content of panoramic scenes for visual navigation? A computational investigation.
abstract: The visual systems of animals have to provide information to guide behaviour and the informational requirements of an animal's behavioural repertoire are often reflected in its sensory system. For insects, this is often evident in the optical array of the compound eye. One behaviour that insects share with many animals is the use of learnt visual information for navigation. As ants are expert visual navigators it may be that their vision is optimised for navigation. Here we take a computational approach in asking how the details of the optical array influence the informational content of scenes used in simple view matching strategies for orientation. We find that robust orientation is best achieved with low-resolution visual information and a large field of view, similar to the optical properties seen for many ant species. A lower resolution allows for a trade-off between specificity and generalisation for stored views. Additionally, our simulations show that orientation performance increases if different portions of the visual field are considered as discrete visual sensors, each giving an independent directional estimate. This suggests that ants might benefit by processing information from their two eyes independently.
authors.affiliation: School of Informatics, University of Edinburgh, Edinburgh, UK.|Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, UK.
authors.forename: Antoine
authors.initials: A
authors.lastname: Wystrach
authors.affiliation: Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, UK.
authors.forename: Alex
authors.initials: A
authors.lastname: Dewar
authors.affiliation: Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Philippides
authors.affiliation: Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, UK. paulgr@sussex.ac.uk.
authors.forename: Paul
authors.initials: P
authors.lastname: Graham
mesh_terms: D000818:Animals; D003198:Computer Simulation; D065854:Spatial Navigation / Q000502:physiology*; D014785:Vision, Ocular / Q000502:physiology*; D014794:Visual Fields / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology*
keywords: Ants; Image matching; Route navigation; Snapshot; View-based homing