September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Does face-drawing experience enhance face processing abilities? Evidence from hidden Markov modeling of eye movements
Author Affiliations
  • Janet Hsiao
    Department of Psychology, University of Hong Kong
  • Hui Fei Chan
    Department of Psychology, University of Hong Kong
  • Tze Kwan Li
    Department of Psychology, University of Hong Kong
  • Antoni Chan
    Department of Computer Science, City University of Hong Kong
Journal of Vision September 2018, Vol.18, 561. doi:10.1167/18.10.561
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      Janet Hsiao, Hui Fei Chan, Tze Kwan Li, Antoni Chan; Does face-drawing experience enhance face processing abilities? Evidence from hidden Markov modeling of eye movements. Journal of Vision 2018;18(10):561. doi: 10.1167/18.10.561.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Recent research has suggested the importance of part-based information in face recognition in addition to global information. Consistent with this finding, eye movement patterns that focus on individual eyes in addition to the face center (analytic patterns) were associated with better recognition performance (Chuk et al., 2017). Nevertheless, face drawing experience was reported to enhance selective attention to face parts but not face recognition performance (Zhou et al., 2012; Tree et al., 2017), presenting a counter example. Here we examined whether eye movement patterns and performances in simultaneous face matching, face recognition (old/new judgment), and part-whole effect (whole face advantage) were modulated by face drawing experience through the Eye Movement analysis with Hidden Markov Models (EMHMM) approach. This approach summarizes an individual's eye movements in terms of personalized regions of interest (ROIs) and transition probabilities among the ROIs using a hidden Markov model (HMM), and similarities among individual HMMs can be quantitatively assessed through log-likelihood measures. We recruited 39 face artists and 39 matched novices. Through clustering participants' eye movement HMMs, we discovered analytic (focusing more on the eyes) and holistic patterns (focusing more on the face center) in all three tasks. Face artists adopted patterns that were more analytic and had better performance than novices in face matching, and participants' drawing ratings were correlated with both eye movement similarity to analytic patterns and face matching performance. In contrast, although in general analytic patterns were associated with better face recognition performance and increased part advantage, artists and novices did not differ in eye movements, recognition performance, or part-whole effect. These results confirm the importance of retrieving part-based information in addition to global information through analytic eye movement patterns in face processing, and suggest that face artists' advantage in face processing is limited to perceptual judgments similar to their drawing experience.

Meeting abstract presented at VSS 2018

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