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  Can fly tangential neurons be used to estimate self-motion?

Franz, M., Neumann, T., Plagge, M., Mallot, H., & Zell, A. (1999). Can fly tangential neurons be used to estimate self-motion? In Ninth International Conference on Artificial Neural Networks ICANN 99 (pp. 994-999). London, UK: Institute of Electrical Engineers.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E65F-1 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-C156-0
Genre: Conference Paper

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https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=818067 (Publisher version)
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 Creators:
Franz, MO1, 2, Author           
Neumann, TR1, 2, Author           
Plagge, M, Author
Mallot, HA1, 2, Author           
Zell, A, Author
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: The so-called tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion. This suggests a possible involvement in the self-motion estimation process. In this study, we examine whether a simplified matched filter model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal matched filter incorporating both the noise properties of the motion signal, and prior knowledge about the distance distribution of the invironment. Tests on a mobile robot demonstrate that the matched filter approach works for real time camera input and the noisy motion fields computed by Reichardt motion detectors.

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 Dates: 1999-09
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1049/cp:19991242
BibTex Citekey: 189
 Degree: -

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Title: Ninth International Conference on Artificial Neural Networks (ICANN 1999)
Place of Event: Edinburgh, UK
Start-/End Date: 1999-09-07 - 1999-09-10

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Title: Ninth International Conference on Artificial Neural Networks ICANN 99
Source Genre: Proceedings
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Publ. Info: London, UK : Institute of Electrical Engineers
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 994 - 999 Identifier: ISBN: 0-85296-721-7

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Title: Conference publication of the Institution of Electrical Engineers
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Pages: - Volume / Issue: 470 Sequence Number: - Start / End Page: - Identifier: -