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Modelling Visual Change Detection and Identification under Free Viewing Conditions

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  • Ken McAnally
  • Russell Martin

Abstract

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.

Suggested Citation

  • Ken McAnally & Russell Martin, 2016. "Modelling Visual Change Detection and Identification under Free Viewing Conditions," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-16, February.
    • Handle: RePEc:plo:pone00:0149217
    DOI: 10.1371/journal.pone.0149217
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    References listed on IDEAS

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    1. Steven J. Luck & Edward K. Vogel, 1997. "The capacity of visual working memory for features and conjunctions," Nature, Nature, vol. 390(6657), pages 279-281, November.
    2. Weiwei Zhang & Steven J. Luck, 2008. "Discrete fixed-resolution representations in visual working memory," Nature, Nature, vol. 453(7192), pages 233-235, May.
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    Cited by:

    1. Fion Choi Hung Lee & Siu Shing Man & Alan Hoi Shou Chan, 2019. "Effects of magnification modes and location cues on visual inspection performance," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-16, March.

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