Refactoring Facial Expressions: an Automatic Analysis of Natural Occurring Facial Expressions in Iterative Social Dilemma (bibtex)
by Giota Stratou, Job Van Der Schalk, Rens Hoegen, Jonathan Gratch
Abstract:
Many automatic facial expression recognizers now output individual facial action units (AUs), but several lines of evidence suggest that it is the combination of AUs that is psychologically meaningful: e.g., (a) constraints arising from facial morphology, (b) prior published evidence, (c) claims arising from basic emotion theory. We performed factor analysis on a large data set and recovered factors that have been discussed in the literature as psychologically meaningful. Further we show that some of these factors have external validity in that they predict participant behaviors in an iterated prisoner’s dilemma task and in fact with more precision than the individual AUs. These results both reinforce the validity of automatic recognition (as these factors would be expected from accurate AU detection) and suggest the benefits of using such factors for understanding these facial expressions as social signals.
Reference:
Refactoring Facial Expressions: an Automatic Analysis of Natural Occurring Facial Expressions in Iterative Social Dilemma (Giota Stratou, Job Van Der Schalk, Rens Hoegen, Jonathan Gratch), In Proceedings of the 7th International Conference on Affective Computing and Intelligent Interaction, 2017.
Bibtex Entry:
@inproceedings{stratou_refactoring_2017,
	address = {San Antonio, TX},
	title = {Refactoring {Facial} {Expressions}: an {Automatic} {Analysis} of {Natural} {Occurring} {Facial} {Expressions} in {Iterative} {Social} {Dilemma}},
	url = {http://ict.usc.edu/pubs/Refactoring%20Facial%20Expressions-an%20Automatic%20Analysis%20of%20Natural%20Occurring%20Facial.pdf},
	abstract = {Many automatic facial expression recognizers now output individual facial action units (AUs), but several lines of evidence suggest that it is the combination of AUs that is psychologically meaningful: e.g., (a) constraints arising from facial morphology, (b) prior published evidence, (c) claims arising from basic emotion theory. We performed factor analysis on a large data set and recovered factors that have been discussed in the literature as psychologically meaningful. Further we show that some of these factors have external validity in that they predict participant behaviors in an iterated prisoner’s dilemma task and in fact with more precision than the individual AUs. These results both reinforce the validity of automatic recognition (as these factors would be expected from accurate AU detection) and suggest the benefits of using such factors for understanding these facial expressions as social signals.},
	booktitle = {Proceedings of the 7th {International} {Conference} on {Affective} {Computing} and {Intelligent} {Interaction}},
	author = {Stratou, Giota and Van Der Schalk, Job and Hoegen, Rens and Gratch, Jonathan},
	month = oct,
	year = {2017},
	keywords = {UARC, Virtual Humans}
}
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