September 2015
Volume 15, Issue 12
Free
Vision Sciences Society Annual Meeting Abstract  |   September 2015
3D OBJECT RECOGNITION IN HONEYBEES
Author Affiliations
  • Annette Werner
    Institute for Ophthalmic Research, University of Tuebingen, Germany
  • Wolfgang Stürzl
    Institute of Robotics and Mechatronics, German Aerospace Center, Germany
  • Johannes Zanker
    Department of Psychology, Royal Holloway University of London, UK
Journal of Vision September 2015, Vol.15, 1105. doi:10.1167/15.12.1105
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      Annette Werner, Wolfgang Stürzl, Johannes Zanker; 3D OBJECT RECOGNITION IN HONEYBEES. Journal of Vision 2015;15(12):1105. doi: 10.1167/15.12.1105.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Bees are one of the best studied animal models for vision and show an amazing complexity of visual performances, given their tiny brains. The recognition of 3D objects is an important and challenging visual task for bees as it is for humans, but like most insects bees lack sufficient stereo vision; how, then, do bees master 3D object recognition? To find out, we trained individual free flying honeybees to collect sugar water from small three-dimensional objects and tested their discrimination. We show that bees successfully encode the three-dimensional form of these objects, whereby they employ an active strategy to uncover the depth profiles. Analysing the bees’ flight tracks revealed specific combinations of flight maneuvers (translations and in-plane rotations). We modelled the generated optic flow patterns and found that their flight maneuvers allows the bees to extract detailed depth cues from amplitude and direction of the image shift. The robustness and simplicity of this strategy offers an efficient solution for 3D- object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.

Meeting abstract presented at VSS 2015

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