Sensitivity to the proportions of faces that vary in human likeness
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Green et al. (2008) demonstrated that individuals show greater agreement when judging the "best looking" facial proportions of human rather than artificial faces.
“One previous study (Green et al., 2008) demonstrated that individuals show greater agreement when judging the “best looking” facial proportions of human rather than artificial faces.”
From A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness (2015) · cites this paper as Green et al., 2008
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Too real for comfort? Uncanny responses to computer generated faces
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- Authors
- Green, R. D., MacDorman, K. F., Ho, C.-C., & Vasudevan, S.
- Affiliations
- Indiana University Indianapolis (US)
- Corresponding author
- MacDorman, Karl F.
- ORCID
- MacDorman, Karl F.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2008-09
- Volume
- 24
- Issue
- 5
- Pages
- 2456-2474
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W1991405702
- Cited by
- 102
- References
- 29
- Citations by year
- 2025: 4 · 2024: 8 · 2023: 6 · 2022: 12 · 2021: 7 · 2020: 6 · 2019: 7 · 2018: 2 · 2017: 4 · 2016: 4 · 2015: 10 · 2014: 10 · 2013: 4 · 2012: 1
- FWCI
- 7.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers in Human Behavior (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Evolutionary Psychology and Human Behavior
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- facial proportions, human-likeness, facial attractiveness, human perception, Android, video game design, virtual reality, human-robot interaction
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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