Constraining a bayesian model of human visual speed perception

Alan A. Stocker, Eero Simoncelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It has been demonstrated that basic aspects of human visual motion perception are qualitatively consistent with a Bayesian estimation framework, where the prior probability distribution on velocity favors slow speeds. Here, we present a refined probabilistic model that can account for the typical trial-to-trial variabilities observed in psychophysical speed perception experiments. We also show that data from such experiments can be used to constrain both the likelihood and prior functions of the model. Specifically, we measured matching speeds and thresholds in a two-alternative forced choice speed discrimination task. Parametric fits to the data reveal that the likelihood function is well approximated by a LogNormal distribution with a characteristic contrast-dependent variance, and that the prior distribution on velocity exhibits significantly heavier tails than a Gaussian, and approximately follows a power-law function.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004
PublisherNeural information processing systems foundation
ISBN (Print)0262195348, 9780262195348
StatePublished - 2005
Event18th Annual Conference on Neural Information Processing Systems, NIPS 2004 - Vancouver, BC, Canada
Duration: Dec 13 2004Dec 16 2004

Other

Other18th Annual Conference on Neural Information Processing Systems, NIPS 2004
CountryCanada
CityVancouver, BC
Period12/13/0412/16/04

Fingerprint

Probability distributions
Experiments
Statistical Models

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

Cite this

Stocker, A. A., & Simoncelli, E. (2005). Constraining a bayesian model of human visual speed perception. In Advances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004 Neural information processing systems foundation.

Constraining a bayesian model of human visual speed perception. / Stocker, Alan A.; Simoncelli, Eero.

Advances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004. Neural information processing systems foundation, 2005.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Stocker, AA & Simoncelli, E 2005, Constraining a bayesian model of human visual speed perception. in Advances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004. Neural information processing systems foundation, 18th Annual Conference on Neural Information Processing Systems, NIPS 2004, Vancouver, BC, Canada, 12/13/04.
Stocker AA, Simoncelli E. Constraining a bayesian model of human visual speed perception. In Advances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004. Neural information processing systems foundation. 2005
Stocker, Alan A. ; Simoncelli, Eero. / Constraining a bayesian model of human visual speed perception. Advances in Neural Information Processing Systems 17 - Proceedings of the 2004 Conference, NIPS 2004. Neural information processing systems foundation, 2005.
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