The Role of Eye Movement Consistency in Learning to Recognise Faces : Computational and Experimental Examinations

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

8 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publicationProceedings for the 42nd Annual Meeting of the Cognitive Science Society
Subtitle of host publicationDeveloping a Mind: Learning in Humans, Animals, and Machines
PublisherThe Cognitive Science Society
Pages1072-1078
Publication statusPublished - Jul 2020

Publication series

NameProceedings for the Annual Meeting of the Cognitive Science Society, CogSci

Conference

Title42nd Annual Meeting of the Cognitive Science Society (CogSci 2020)
LocationVirtual
Period29 July - 1 August 2020

Abstract

In face recognition, the frequency of looking at the eyes, the most diagnostic feature, predicts better performance in adults but not in children, suggesting that different factors may underlie children’s face recognition performance. Here we test the hypothesis that eye movement consistency plays an important role during early learning stages. Through computational modelling that combines a deep neural network and a hidden Markov model that learns eye movement strategies by interacting with the network, we showed that consistency instead of eye movement pattern better predicted face recognition performance during early learning stages. Similarly, in human studies, children’s consistency but not pattern of eye movements predicted face recognition performance, and their eye movement consistency was associated with executive function abilities. Thus, learning to recognise faces initially involves developing a consistent visual routine, which depends on executive function abilities. This finding has important implications for learning in both healthy and clinical populations.

Research Area(s)

  • Eye movement, face recognition, deep neural network, hidden Markov model, entropy

Citation Format(s)

The Role of Eye Movement Consistency in Learning to Recognise Faces: Computational and Experimental Examinations . / Hsiao, Janet H.; An, Jeehye; Chan, Antoni B.
Proceedings for the 42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines. The Cognitive Science Society, 2020. p. 1072-1078 (Proceedings for the Annual Meeting of the Cognitive Science Society, CogSci).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review