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What We Can Learn From the Primate’s Visual System

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Abstract

In this review, we discuss the impact (or lack thereof) biologically motivated vision has had on computer vision in the last decades. We then summarize a number of computer vision and robotic problems for which biological models can give indications for how these can be addressed. Then we summarize important findings about the primate’s visual system and draw a number of conclusions for the development of algorithms from these findings.

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Notes

  1. Actually it has mostly been the macaque’s visual system that is the basis for neuro-physiological investigations which however shows a large degree of similarity to the human visual system.

  2. An area is called retinotopically organized when it preserves the neighbourhood relations of the retina, i.e., the general arrangement of 2D positions. In particular the cortical areas at lower levels of the visual hierarchy are retinotopic.

  3. The receptive field associated to a neuron is the part of the visual field that directly influences the response of the neuron.

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Acknowledgments

Norbert Krüger was supported by the EU Cognitive Systems project XPERIENCE (FP7-ICT-270273) and the DSF project patient@home. Michael Zillich was supported by EU projects SQUIRREL (FP7-ICT-610532) and STRANDS (FP7-ICT-600623) and Austrian Science Fund (FWF) grant No. TRP 139-N23 InSitu. Many thanks to Antonio Rodriguez Sanchez for his work on Fig. 1 and Laurenz Wiskott for his work on Fig. 2. Many thanks also to IEEE for allowing to re-use these figures from [48].

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  1. The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark

    Norbert Krüger & Anders Glent Buch

  2. Automation and Control Institute, Vienna University of Technology, Vienna, Austria

    Michael Zillich

  3. Laboratorium voor Neuro- en Psychofysiologie KU Leuven, Louvain, Belgium

    Peter Janssen

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  1. Norbert Krüger
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Correspondence to Michael Zillich.

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Krüger, N., Zillich, M., Janssen, P. et al. What We Can Learn From the Primate’s Visual System. Künstl Intell 29, 9–18 (2015). https://doi.org/10.1007/s13218-014-0345-9

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