Source abstract
Abstract
Jumping spiders are capable of estimating the distance to their prey relying only on the information from one of their main eyes. Recently, it has been shown that jumping spiders perform this estimation based on image defocus cues. In order to gain insight into the mechanisms involved in this blur-to-distance mapping as performed by the spider and to judge whether inspirations can be drawn from spider vision for depth-from-defocus computer vision algorithms, we constructed a three-dimensional (3D) model of the anterior median eye of the Metaphidippus aeneolus, a well studied species of jumping spider. We were able to study images of the environment as the spider would see them and to measure the performances of a well known depth-from-defocus algorithm on this dataset. We found that the algorithm performs best when using images that are averaged over the considerable thickness of the spider’s receptor layers, thus pointing towards a possible functional role of the receptor thickness for the spider’s depth estimation capabilities.
Source: crossref · Quality: baseline
Affiliations
Bernstein Center for Computational Neuroscience Berlin, Unter den Linden 6, 10099 Berlin, Germany
Robotics Innovation Center, German Research Center for Artificial Intelligence, 28359 Bremen, Germany
Advanced Concepts Team, European Space Agency, 2200AG Noordwijk, The Netherlands
Adaptive Systems Group, Department of Computer Science, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
Polymer Chemistry & Biomaterials Research Group, Department of Organic and Macromolecular Chemistry, Ghent University, Krijgslaan 281 S4Bis, B-9000 Ghent, Belgium
References (10)
Show source-provided references
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