Cargando…

Modelling human visual navigation using multi-view scene reconstruction

It is often assumed that humans generate a 3D reconstruction of the environment, either in egocentric or world-based coordinates, but the steps involved are unknown. Here, we propose two reconstruction-based models, evaluated using data from two tasks in immersive virtual reality. We model the obser...

Descripción completa

Detalles Bibliográficos
Autores principales: Pickup, Lyndsey C., Fitzgibbon, Andrew W., Glennerster, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3755223/
https://www.ncbi.nlm.nih.gov/pubmed/23778937
http://dx.doi.org/10.1007/s00422-013-0558-2
_version_ 1782281964171034624
author Pickup, Lyndsey C.
Fitzgibbon, Andrew W.
Glennerster, Andrew
author_facet Pickup, Lyndsey C.
Fitzgibbon, Andrew W.
Glennerster, Andrew
author_sort Pickup, Lyndsey C.
collection PubMed
description It is often assumed that humans generate a 3D reconstruction of the environment, either in egocentric or world-based coordinates, but the steps involved are unknown. Here, we propose two reconstruction-based models, evaluated using data from two tasks in immersive virtual reality. We model the observer’s prediction of landmark location based on standard photogrammetric methods and then combine location predictions to compute likelihood maps of navigation behaviour. In one model, each scene point is treated independently in the reconstruction; in the other, the pertinent variable is the spatial relationship between pairs of points. Participants viewed a simple environment from one location, were transported (virtually) to another part of the scene and were asked to navigate back. Error distributions varied substantially with changes in scene layout; we compared these directly with the likelihood maps to quantify the success of the models. We also measured error distributions when participants manipulated the location of a landmark to match the preceding interval, providing a direct test of the landmark-location stage of the navigation models. Models such as this, which start with scenes and end with a probabilistic prediction of behaviour, are likely to be increasingly useful for understanding 3D vision.
format Online
Article
Text
id pubmed-3755223
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-37552232013-09-05 Modelling human visual navigation using multi-view scene reconstruction Pickup, Lyndsey C. Fitzgibbon, Andrew W. Glennerster, Andrew Biol Cybern Original Paper It is often assumed that humans generate a 3D reconstruction of the environment, either in egocentric or world-based coordinates, but the steps involved are unknown. Here, we propose two reconstruction-based models, evaluated using data from two tasks in immersive virtual reality. We model the observer’s prediction of landmark location based on standard photogrammetric methods and then combine location predictions to compute likelihood maps of navigation behaviour. In one model, each scene point is treated independently in the reconstruction; in the other, the pertinent variable is the spatial relationship between pairs of points. Participants viewed a simple environment from one location, were transported (virtually) to another part of the scene and were asked to navigate back. Error distributions varied substantially with changes in scene layout; we compared these directly with the likelihood maps to quantify the success of the models. We also measured error distributions when participants manipulated the location of a landmark to match the preceding interval, providing a direct test of the landmark-location stage of the navigation models. Models such as this, which start with scenes and end with a probabilistic prediction of behaviour, are likely to be increasingly useful for understanding 3D vision. Springer Berlin Heidelberg 2013-06-19 2013 /pmc/articles/PMC3755223/ /pubmed/23778937 http://dx.doi.org/10.1007/s00422-013-0558-2 Text en © The Author(s) 2013 https://creativecommons.org/licenses/by/2.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Original Paper
Pickup, Lyndsey C.
Fitzgibbon, Andrew W.
Glennerster, Andrew
Modelling human visual navigation using multi-view scene reconstruction
title Modelling human visual navigation using multi-view scene reconstruction
title_full Modelling human visual navigation using multi-view scene reconstruction
title_fullStr Modelling human visual navigation using multi-view scene reconstruction
title_full_unstemmed Modelling human visual navigation using multi-view scene reconstruction
title_short Modelling human visual navigation using multi-view scene reconstruction
title_sort modelling human visual navigation using multi-view scene reconstruction
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3755223/
https://www.ncbi.nlm.nih.gov/pubmed/23778937
http://dx.doi.org/10.1007/s00422-013-0558-2
work_keys_str_mv AT pickuplyndseyc modellinghumanvisualnavigationusingmultiviewscenereconstruction
AT fitzgibbonandreww modellinghumanvisualnavigationusingmultiviewscenereconstruction
AT glennersterandrew modellinghumanvisualnavigationusingmultiviewscenereconstruction