Validating a model of architectural hazard visibility with low-vision observers.

Pedestrians with low vision are at risk of injury when hazards, such as steps and posts, have low visibility. This study aims at validating the software implementation of a computational model that estimates hazard visibility. The model takes as input a photorealistic 3D rendering of an architectura...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Siyun Liu, Yichen Liu, Daniel J Kersten, Robert A Shakespeare, William B Thompson, Gordon E Legge
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6e4ace2c065f4a7e8257abb5650181ac
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6e4ace2c065f4a7e8257abb5650181ac
record_format	dspace
spelling	oai:doaj.org-article:6e4ace2c065f4a7e8257abb5650181ac2021-12-02T20:16:18ZValidating a model of architectural hazard visibility with low-vision observers.1932-620310.1371/journal.pone.0260267https://doaj.org/article/6e4ace2c065f4a7e8257abb5650181ac2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0260267https://doaj.org/toc/1932-6203Pedestrians with low vision are at risk of injury when hazards, such as steps and posts, have low visibility. This study aims at validating the software implementation of a computational model that estimates hazard visibility. The model takes as input a photorealistic 3D rendering of an architectural space, and the acuity and contrast sensitivity of a low-vision observer, and outputs estimates of the visibility of hazards in the space. Our experiments explored whether the model could predict the likelihood of observers correctly identifying hazards. In Experiment 1, we tested fourteen normally sighted subjects with blur goggles that simulated moderate or severe acuity reduction. In Experiment 2, we tested ten low-vision subjects with moderate to severe acuity reduction. Subjects viewed computer-generated images of a walkway containing five possible targets ahead-big step-up, big step-down, small step-up, small step-down, or a flat continuation. Each subject saw these stimuli with variations of lighting and viewpoint in 250 trials and indicated which of the five targets was present. The model generated a score on each trial that estimated the visibility of the target. If the model is valid, the scores should be predictive of how accurately the subjects identified the targets. We used logistic regression to examine the correlation between the scores and the participants' responses. For twelve of the fourteen normally sighted subjects with artificial acuity reduction and all ten low-vision subjects, there was a significant relationship between the scores and the participant's probability of correct identification. These experiments provide evidence for the validity of a computational model that predicts the visibility of architectural hazards. It lays the foundation for future validation of this hazard evaluation tool, which may be useful for architects to assess the visibility of hazards in their designs, thereby enhancing the accessibility of spaces for people with low vision.Siyun LiuYichen LiuDaniel J KerstenRobert A ShakespeareWilliam B ThompsonGordon E LeggePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0260267 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Siyun Liu Yichen Liu Daniel J Kersten Robert A Shakespeare William B Thompson Gordon E Legge Validating a model of architectural hazard visibility with low-vision observers.
description	Pedestrians with low vision are at risk of injury when hazards, such as steps and posts, have low visibility. This study aims at validating the software implementation of a computational model that estimates hazard visibility. The model takes as input a photorealistic 3D rendering of an architectural space, and the acuity and contrast sensitivity of a low-vision observer, and outputs estimates of the visibility of hazards in the space. Our experiments explored whether the model could predict the likelihood of observers correctly identifying hazards. In Experiment 1, we tested fourteen normally sighted subjects with blur goggles that simulated moderate or severe acuity reduction. In Experiment 2, we tested ten low-vision subjects with moderate to severe acuity reduction. Subjects viewed computer-generated images of a walkway containing five possible targets ahead-big step-up, big step-down, small step-up, small step-down, or a flat continuation. Each subject saw these stimuli with variations of lighting and viewpoint in 250 trials and indicated which of the five targets was present. The model generated a score on each trial that estimated the visibility of the target. If the model is valid, the scores should be predictive of how accurately the subjects identified the targets. We used logistic regression to examine the correlation between the scores and the participants' responses. For twelve of the fourteen normally sighted subjects with artificial acuity reduction and all ten low-vision subjects, there was a significant relationship between the scores and the participant's probability of correct identification. These experiments provide evidence for the validity of a computational model that predicts the visibility of architectural hazards. It lays the foundation for future validation of this hazard evaluation tool, which may be useful for architects to assess the visibility of hazards in their designs, thereby enhancing the accessibility of spaces for people with low vision.
format	article
author	Siyun Liu Yichen Liu Daniel J Kersten Robert A Shakespeare William B Thompson Gordon E Legge
author_facet	Siyun Liu Yichen Liu Daniel J Kersten Robert A Shakespeare William B Thompson Gordon E Legge
author_sort	Siyun Liu
title	Validating a model of architectural hazard visibility with low-vision observers.
title_short	Validating a model of architectural hazard visibility with low-vision observers.
title_full	Validating a model of architectural hazard visibility with low-vision observers.
title_fullStr	Validating a model of architectural hazard visibility with low-vision observers.
title_full_unstemmed	Validating a model of architectural hazard visibility with low-vision observers.
title_sort	validating a model of architectural hazard visibility with low-vision observers.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/6e4ace2c065f4a7e8257abb5650181ac
work_keys_str_mv	AT siyunliu validatingamodelofarchitecturalhazardvisibilitywithlowvisionobservers AT yichenliu validatingamodelofarchitecturalhazardvisibilitywithlowvisionobservers AT danieljkersten validatingamodelofarchitecturalhazardvisibilitywithlowvisionobservers AT robertashakespeare validatingamodelofarchitecturalhazardvisibilitywithlowvisionobservers AT williambthompson validatingamodelofarchitecturalhazardvisibilitywithlowvisionobservers AT gordonelegge validatingamodelofarchitecturalhazardvisibilitywithlowvisionobservers
_version_	1718374531524984832

Validating a model of architectural hazard visibility with low-vision observers.

Ejemplares similares