504
Views
12
CrossRef citations to date
0
Altmetric
Full articles

Perceiving facial expressions

&
Pages 373-411 | Received 01 Jul 2007, Published online: 20 Mar 2009
 

Abstract

Three experiments investigated the perception of facial displays of emotions. Using a morphing technique, Experiment 1 (identification task) and Experiment 2 (ABX discrimination task) evaluated the merits of categorical and dimensional models of the representation of these stimuli. We argue that basic emotions—as they are usually defined verbally—do not correspond to primary perceptual categories emerging from the visual analysis of facial expressions. Instead, the results are compatible with the hypothesis that facial expressions are coded in a continuous anisotropic space structured by valence axes. Experiment 3 (identification task) introduces a new technique for generating chimeras to address the debate between feature-based and holistic models of the processing of facial expressions. Contrary to the pure holistic hypothesis, the results suggest that an independent assessment of discrimination features is possible, and may be sufficient for identifying expressions even when the global facial configuration is ambiguous. However, they also suggest that top-down processing may improve identification accuracy by assessing the coherence of local features.

Acknowledgements

This research was supported by an FNRS Grant and COFIN (Italian Ministry of University and Research) Grant No. 2005119851_003 to Paolo Viviani.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 238.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.