Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion

Guo, Kun and Soornack, Yoshi and Settle, Rebecca (2019) Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion. Vision Research, 157 . pp. 112-122. ISSN 0042-6989

Full content URL: http://doi.org/10.1016/j.visres.2018.02.001

Documents
Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion
Accepted Manuscript
[img]
[Download]
[img]
Preview
PDF
31317 MS-face quality-R1.pdf - Whole Document

589kB
Item Type:Article
Item Status:Live Archive

Abstract

Our capability of recognizing facial expressions of emotion under different viewing conditions implies the existence of an invariant expression representation. As natural visual signals are often distorted and our perceptual strategy changes with external noise level, it is essential to understand how expression perception is susceptible to face distortion and whether the same facial cues are used to process high- and low-quality face images. We systematically manipulated face image resolution (experiment 1) and blur (experiment 2), and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. Our analysis revealed a reasonable tolerance to face distortion in expression perception. Reducing image resolution up to 48 × 64 pixels or increasing image blur up to 15 cycles/image had little impact on expression assessment and associated gaze behaviour. Further distortion led to decreased expression categorization accuracy and intensity rating, increased reaction time and fixation duration, and stronger central fixation bias which was not driven by distortion-induced changes in local image saliency. Interestingly, the observed distortion effects were expression-dependent with less deterioration impact on happy and surprise expressions, suggesting this distortion-invariant facial expression perception might be achieved through the categorical model involving a non-linear configural combination of local facial features. [Abstract copyright: Copyright © 2018 Elsevier Ltd. All rights reserved.]

Keywords:Facial expression, Image resolution, Image blur, Expression categorization, Expression intensity, Gaze behaviour
Subjects:C Biological Sciences > C850 Cognitive Psychology
Divisions:College of Social Science > School of Psychology
ID Code:31317
Deposited On:10 Apr 2018 10:57

Repository Staff Only: item control page