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  Bayesian motion estimation accounts for a surprising bias in 3D vision

Welchman, A., Lam, J., & Bülthoff, H. (2008). Bayesian motion estimation accounts for a surprising bias in 3D vision. Proceedings of the National Academy of Sciences of the United States of America, 105(33), 12087-12092. doi:10.1073/pnas.0804378105.

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Welchman, AE, Author           
Lam, JM1, 2, Author           
Bülthoff, HH1, 2, 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, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Determining the approach of a moving object is a vital survival skill that depends on the brain combining information about lateral translation and motion-in-depth. Given the importance of sensing motion for obstacle avoidance, it is surprising that humans make errors, reporting an object will miss them when it is on a collision course with their head. Here we provide evidence that biases observed when participants estimate movement in depth result from the brainamp;lsquo;s use of a “prior” favoring slow velocity. We formulate a Bayesian model for computing 3D motion using independently estimated parameters for the shape of the visual systemamp;lsquo;s slow velocity prior. We demonstrate the success of this model in accounting for human behavior in separate experiments that assess both sensitivity and bias in 3D motion estimation. Our results show that a surprising perceptual error in 3D motion perception reflects the importance of prior probabilities when estimating
environm
ental pr
operties.

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 Dates: 2008-08
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1073/pnas.0804378105
BibTex Citekey: 5326
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Title: Proceedings of the National Academy of Sciences of the United States of America
  Other : Proc. Acad. Sci. USA
  Other : Proc. Acad. Sci. U.S.A.
  Other : Proceedings of the National Academy of Sciences of the USA
  Abbreviation : PNAS
Source Genre: Journal
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Publ. Info: Washington, D.C. : National Academy of Sciences
Pages: - Volume / Issue: 105 (33) Sequence Number: - Start / End Page: 12087 - 12092 Identifier: ISSN: 0027-8424
CoNE: https://pure.mpg.de/cone/journals/resource/954925427230