Modelling Visual Change Detection and Identification under Free Viewing Conditions.

We examined whether the abilities of observers to perform an analogue of a real-world monitoring task involving detection and identification of changes to items in a visual display could be explained better by models based on signal detection theory (SDT) or high threshold theory (HTT). Our study di...

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Main Authors: Ken McAnally, Russell Martin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4755572?pdf=render
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spelling doaj-aee4f3a79f014939822d55f35d2d6a4e2020-11-25T01:24:09ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01112e014921710.1371/journal.pone.0149217Modelling Visual Change Detection and Identification under Free Viewing Conditions.Ken McAnallyRussell MartinWe examined whether the abilities of observers to perform an analogue of a real-world monitoring task involving detection and identification of changes to items in a visual display could be explained better by models based on signal detection theory (SDT) or high threshold theory (HTT). Our study differed from most previous studies in that observers were allowed to inspect the initial display for 3s, simulating the long inspection times typical of natural viewing, and their eye movements were not constrained. For the majority of observers, combined change detection and identification performance was best modelled by a SDT-based process that assumed that memory resources were distributed across all eight items in our displays. Some observers required a parameter to allow for sometimes making random guesses at the identities of changes they had missed. However, the performance of a small proportion of observers was best explained by a HTT-based model that allowed for lapses of attention.http://europepmc.org/articles/PMC4755572?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Ken McAnally
Russell Martin
spellingShingle Ken McAnally
Russell Martin
Modelling Visual Change Detection and Identification under Free Viewing Conditions.
PLoS ONE
author_facet Ken McAnally
Russell Martin
author_sort Ken McAnally
title Modelling Visual Change Detection and Identification under Free Viewing Conditions.
title_short Modelling Visual Change Detection and Identification under Free Viewing Conditions.
title_full Modelling Visual Change Detection and Identification under Free Viewing Conditions.
title_fullStr Modelling Visual Change Detection and Identification under Free Viewing Conditions.
title_full_unstemmed Modelling Visual Change Detection and Identification under Free Viewing Conditions.
title_sort modelling visual change detection and identification under free viewing conditions.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description We examined whether the abilities of observers to perform an analogue of a real-world monitoring task involving detection and identification of changes to items in a visual display could be explained better by models based on signal detection theory (SDT) or high threshold theory (HTT). Our study differed from most previous studies in that observers were allowed to inspect the initial display for 3s, simulating the long inspection times typical of natural viewing, and their eye movements were not constrained. For the majority of observers, combined change detection and identification performance was best modelled by a SDT-based process that assumed that memory resources were distributed across all eight items in our displays. Some observers required a parameter to allow for sometimes making random guesses at the identities of changes they had missed. However, the performance of a small proportion of observers was best explained by a HTT-based model that allowed for lapses of attention.
url http://europepmc.org/articles/PMC4755572?pdf=render
work_keys_str_mv AT kenmcanally modellingvisualchangedetectionandidentificationunderfreeviewingconditions
AT russellmartin modellingvisualchangedetectionandidentificationunderfreeviewingconditions
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