---
_id: '6075'
abstract:
- lang: eng
  text: For almost three decades, the theory of visual attention (TVA) has been successful
    in mathematically describing and explaining a wide variety of phenomena in visual
    selection and recognition with high quantitative precision. Interestingly, the
    influence of feature contrast on attention has been included in TVA only recently,
    although it has been extensively studied outside the TVA framework. The present
    approach further develops this extension of TVA’s scope by measuring and modeling
    salience. An empirical measure of salience is achieved by linking different (orientation
    and luminance) contrasts to a TVA parameter. In the modeling part, the function
    relating feature contrasts to salience is described mathematically and tested
    against alternatives by Bayesian model comparison. This model comparison reveals
    that the power function is an appropriate model of salience growth in the dimensions
    of orientation and luminance contrast. Furthermore, if contrasts from the two
    dimensions are comb
article_type: original
author:
- first_name: Alexander
  full_name: Krüger, Alexander
  last_name: Krüger
- first_name: Jan
  full_name: Tünnermann, Jan
  last_name: Tünnermann
- first_name: Ingrid
  full_name: Scharlau, Ingrid
  id: '451'
  last_name: Scharlau
  orcid: 0000-0003-2364-9489
citation:
  ama: Krüger A, Tünnermann J, Scharlau I. Measuring and modeling salience with the
    theory of visual attention. <i>Attention, Perception, &#38; Psychophysics</i>.
    2017;79(6):1593-1614. doi:<a href="https://doi.org/10.3758/s13414-017-1325-6">10.3758/s13414-017-1325-6</a>
  apa: Krüger, A., Tünnermann, J., &#38; Scharlau, I. (2017). Measuring and modeling
    salience with the theory of visual attention. <i>Attention, Perception, &#38;
    Psychophysics</i>, <i>79</i>(6), 1593–1614. <a href="https://doi.org/10.3758/s13414-017-1325-6">https://doi.org/10.3758/s13414-017-1325-6</a>
  bibtex: '@article{Krüger_Tünnermann_Scharlau_2017, title={Measuring and modeling
    salience with the theory of visual attention.}, volume={79}, DOI={<a href="https://doi.org/10.3758/s13414-017-1325-6">10.3758/s13414-017-1325-6</a>},
    number={6}, journal={Attention, Perception, &#38; Psychophysics}, author={Krüger,
    Alexander and Tünnermann, Jan and Scharlau, Ingrid}, year={2017}, pages={1593–1614}
    }'
  chicago: 'Krüger, Alexander, Jan Tünnermann, and Ingrid Scharlau. “Measuring and
    Modeling Salience with the Theory of Visual Attention.” <i>Attention, Perception,
    &#38; Psychophysics</i> 79, no. 6 (2017): 1593–1614. <a href="https://doi.org/10.3758/s13414-017-1325-6">https://doi.org/10.3758/s13414-017-1325-6</a>.'
  ieee: 'A. Krüger, J. Tünnermann, and I. Scharlau, “Measuring and modeling salience
    with the theory of visual attention.,” <i>Attention, Perception, &#38; Psychophysics</i>,
    vol. 79, no. 6, pp. 1593–1614, 2017, doi: <a href="https://doi.org/10.3758/s13414-017-1325-6">10.3758/s13414-017-1325-6</a>.'
  mla: Krüger, Alexander, et al. “Measuring and Modeling Salience with the Theory
    of Visual Attention.” <i>Attention, Perception, &#38; Psychophysics</i>, vol.
    79, no. 6, 2017, pp. 1593–614, doi:<a href="https://doi.org/10.3758/s13414-017-1325-6">10.3758/s13414-017-1325-6</a>.
  short: A. Krüger, J. Tünnermann, I. Scharlau, Attention, Perception, &#38; Psychophysics
    79 (2017) 1593–1614.
date_created: 2018-12-10T07:05:04Z
date_updated: 2022-06-06T14:08:05Z
department:
- _id: '424'
doi: 10.3758/s13414-017-1325-6
intvolume: '        79'
issue: '6'
keyword:
- Salience
- Visual attention
- Bayesian inference
- Theory of visual attention
- Computational modeling
- Inference
- Object Recognition
- Theories
- Visual Perception
- Visual Attention
- Luminance
- Perceptual Orientation
- Statistical Probability
- Stimulus Salience
- Computational Modeling
language:
- iso: eng
page: 1593 - 1614
publication: Attention, Perception, & Psychophysics
publication_identifier:
  issn:
  - 1943-3921
publication_status: published
status: public
title: Measuring and modeling salience with the theory of visual attention.
type: journal_article
user_id: '42165'
volume: 79
year: '2017'
...