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  • SCC_August_2020

    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Spatial Cognition and Computation on 12/10/2020, available online: https://www.tandfonline.com/doi/full/10.1080/13875868.2020.1830993

    Accepted author manuscript, 1.57 MB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation. / Yesiltepe, Demet; Ozbil Torun, Ayse; Coutrot, Antoine et al.
In: Spatial Cognition and Computation, Vol. 21, No. 1, 01.03.2021.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Yesiltepe, D, Ozbil Torun, A, Coutrot, A, Hornberger, M, Conroy-Dalton, R & Spiers, H 2021, 'Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation', Spatial Cognition and Computation, vol. 21, no. 1. https://doi.org/10.1080/13875868.2020.1830993

APA

Yesiltepe, D., Ozbil Torun, A., Coutrot, A., Hornberger, M., Conroy-Dalton, R., & Spiers, H. (2021). Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation. Spatial Cognition and Computation, 21(1). https://doi.org/10.1080/13875868.2020.1830993

Vancouver

Yesiltepe D, Ozbil Torun A, Coutrot A, Hornberger M, Conroy-Dalton R, Spiers H. Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation. Spatial Cognition and Computation. 2021 Mar 1;21(1). Epub 2020 Oct 12. doi: 10.1080/13875868.2020.1830993

Author

Yesiltepe, Demet ; Ozbil Torun, Ayse ; Coutrot, Antoine et al. / Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation. In: Spatial Cognition and Computation. 2021 ; Vol. 21, No. 1.

Bibtex

@article{5ab20e8348664ae19e184615376f6630,
title = "Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation",
abstract = "In this study, it was aimed to understand whether or not computer models ofsaliency could explain landmark saliency. An online survey was conducted andparticipants were asked to watch videos from a spatial navigation video game(Sea Hero Quest). Participants were asked to pay attention to the environmentswithin which the boat was moving and to rate the perceived saliency of eachlandmark. In addition, state-of-the-art computer saliency models were used toobjectively quantify landmark saliency. No significant relationship was foundbetween objective and subjective saliency measures. This indicates that duringpassive observation of an environment being navigated, current automatedmodels of saliency fail to predict subjective reports of visual attention tolandmarks. ",
keywords = "Landmark, saliency, Object recognition, Spatial knowledge, Virtual reality, Virtual environments",
author = "Demet Yesiltepe and {Ozbil Torun}, Ayse and Antoine Coutrot and Michael Hornberger and Ruth Conroy-Dalton and Hugo Spiers",
note = "This is an Accepted Manuscript of an article published by Taylor & Francis in Spatial Cognition and Computation on 12/10/2020, available online: https://www.tandfonline.com/doi/full/10.1080/13875868.2020.1830993 ",
year = "2021",
month = mar,
day = "1",
doi = "10.1080/13875868.2020.1830993",
language = "English",
volume = "21",
journal = "Spatial Cognition and Computation",
issn = "1387-5868",
publisher = "Taylor and Francis Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation

AU - Yesiltepe, Demet

AU - Ozbil Torun, Ayse

AU - Coutrot, Antoine

AU - Hornberger, Michael

AU - Conroy-Dalton, Ruth

AU - Spiers, Hugo

N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in Spatial Cognition and Computation on 12/10/2020, available online: https://www.tandfonline.com/doi/full/10.1080/13875868.2020.1830993

PY - 2021/3/1

Y1 - 2021/3/1

N2 - In this study, it was aimed to understand whether or not computer models ofsaliency could explain landmark saliency. An online survey was conducted andparticipants were asked to watch videos from a spatial navigation video game(Sea Hero Quest). Participants were asked to pay attention to the environmentswithin which the boat was moving and to rate the perceived saliency of eachlandmark. In addition, state-of-the-art computer saliency models were used toobjectively quantify landmark saliency. No significant relationship was foundbetween objective and subjective saliency measures. This indicates that duringpassive observation of an environment being navigated, current automatedmodels of saliency fail to predict subjective reports of visual attention tolandmarks.

AB - In this study, it was aimed to understand whether or not computer models ofsaliency could explain landmark saliency. An online survey was conducted andparticipants were asked to watch videos from a spatial navigation video game(Sea Hero Quest). Participants were asked to pay attention to the environmentswithin which the boat was moving and to rate the perceived saliency of eachlandmark. In addition, state-of-the-art computer saliency models were used toobjectively quantify landmark saliency. No significant relationship was foundbetween objective and subjective saliency measures. This indicates that duringpassive observation of an environment being navigated, current automatedmodels of saliency fail to predict subjective reports of visual attention tolandmarks.

KW - Landmark

KW - saliency

KW - Object recognition

KW - Spatial knowledge

KW - Virtual reality

KW - Virtual environments

U2 - 10.1080/13875868.2020.1830993

DO - 10.1080/13875868.2020.1830993

M3 - Journal article

VL - 21

JO - Spatial Cognition and Computation

JF - Spatial Cognition and Computation

SN - 1387-5868

IS - 1

ER -