The Effect of Human Avatars' Facial Similarity on Users' Sense of Co-presence

Author(s):  
Doo-Hwang Lee ◽  
Joung-Huem Kwon ◽  
Young-Nam Seo ◽  
Bum-Jae You
Keyword(s):  
Author(s):  
Bettina von Helversen ◽  
Stefan M. Herzog ◽  
Jörg Rieskamp

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.


2015 ◽  
Vol 23 (4) ◽  
pp. 1138-1145 ◽  
Author(s):  
赵俊莉 ZHAO Jun-li ◽  
武仲科 WU Zhong-ke ◽  
刘翠婷 LIU Cui-ting ◽  
段福庆 DUAN Fu-qing ◽  
周明全 ZHOU Ming-quan ◽  
...  

2020 ◽  
Vol 20 (6) ◽  
pp. 18
Author(s):  
Florian Hansen ◽  
Lisa M. DeBruine ◽  
Iris J. Holzleitner ◽  
Anthony J. Lee ◽  
Kieran J. O'Shea ◽  
...  

2006 ◽  
Vol 27 (3) ◽  
pp. 373-385 ◽  
Author(s):  
Jeremy N. Bailenson ◽  
Philip Garland ◽  
Shanto Iyengar ◽  
Nick Yee

2019 ◽  
Author(s):  
Marie JE Charpentier ◽  
Mélanie Harté ◽  
Clémence Poirotte ◽  
Jade Meric de Bellefon ◽  
Benjamin Laubi ◽  
...  

ABSTRACTAnimal faces convey important information such as individual health status1 or identity2,3. Human and nonhuman primates rely on highly heritable facial traits4,5 to recognize their kin6–8. However, whether these facial traits have evolved for this specific function of kin recognition remains unknown. We present the first unambiguous evidence that inter-individual facial similarity has been selected to signal kinship using a state-of-the-art artificial intelligence approach based on deep neural networks and long-term data on a natural population of nonhuman primates. The typical matrilineal society of mandrills, is characterized by an extreme male’s reproductive skew with one male generally siring the large majority of offspring born into the different matrilines each year9. Philopatric females are raised and live throughout their lives with familiar maternal half-sisters (MHS) but because of male’s reproductive monopolization, they also live with unfamiliar paternal half-sisters (PHS). Because kin selection predicts differentiated interactions with kin rather than nonkin10 and that PHS largely outnumber MHS in a mandrills’ social group, natural selection should favour mechanisms to recognize PHS. Here, we first show that PHS socially interact with each other as much as MHS do, both more than nonkin. Second, using artificial intelligence trained to recognize individual mandrills from a database of 16k portrait pictures, we demonstrate that facial similarity increases with genetic relatedness. However, PHS resemble more to each other than MHS do, despite both kin categories sharing similar degrees of genetic relatedness. We propose genomic imprinting as a plausible genetic mechanism to explain paternally-derived facial similarity among PHS selected to improve kin recognition. This study further highlights the potential of artificial intelligence to study evolutionary mechanisms driving variation between phenotypes.


2021 ◽  
Vol 21 (9) ◽  
pp. 1900
Author(s):  
Kamila M. Jozwik ◽  
Jonathan O'Keeffe ◽  
Katherine R. Storrs ◽  
Nikolaus Kriegeskorte

Author(s):  
John McCauley ◽  
Sobhan Soleymani ◽  
Brady Williams ◽  
John Dando ◽  
Nasser Nasrabadi ◽  
...  

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 250-250
Author(s):  
M J Lyons ◽  
K Morikawa ◽  
S Akamatsu

Little is known about how facial representation in the face-selective areas of inferotemporal cortex is built up from the output of earlier visual areas such as primary visual cortex (area V1). We report work on a model of perceived facial similarity based on topographically ordered aggregates of localised, oriented, and spatial-frequency-selective receptive fields characteristic of V1 cells. The receptive fields are approximated with a set of Gabor filters. This Gabor-based code allows representation of the fine differences in texture and configuration needed for facial discrimination processes. Lyons and Morikawa (1996 Investigative Ophthalmology and Visual Science37 910), showed that Gabor-based similarity is a good predictor of facial similarity for comparisons of fairly similar faces but not sufficient to model experience-dependent effects such as the ‘other race effect’. Here we report results of a study on the effects of image negation on facial similarity perception. Negation of image gray levels interferes with face recognition (Bruce and Lanton, 1994 Perception23 803 – 822) while preserving 2-D facial-shape information. The Gabor similarity measure models non-endstopped complex cells of V1 and is not affected by image negation. One group of subjects judged similarity among a set of normal gray-scale facial images while another group judged similarity between negative images of the same stimuli. Agreement between the model and human subjects did not decrease with image negation. Moreover, human similarity ratings between negative faces were strongly correlated with those between positives. These results support Gabor-based similarity as a model for facial similarity perception.


Sign in / Sign up

Export Citation Format

Share Document