Alle Publikationen
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2017
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(2017): Are You Smiling, or Have I Seen You Before? Familiarity Makes Faces Look Happier. In: Psychological science 28 (8), S. 1087-1102. DOI: 10.1177/0956797617702003
DOI: http://www.ncbi.nlm.nih.gov/pubmed/28594281 Abstract: It is clear that unreinforced repetition (familiarization) influences affective responses to social stimuli, but its effects on the perception of facial emotion are unknown. Reporting the results of two experiments, we show for the first time that repeated exposure enhances the perceived happiness of facial expressions. In Experiment 1, using a paradigm in which subjects' responses were orthogonal to happiness in order to avoid response biases, we found that faces of individuals who had previously been shown were deemed happier than novel faces. In Experiment 2, we replicated this effect with a rapid "happy or angry" categorization task. Using psychometric function fitting, we found that for subjects to classify a face as happy, they needed less actual happiness to be present in the face if the target was familiar than if it was novel. Critically, our results suggest that familiar faces appear happier than novel faces because familiarity selectively enhances the impact of positive stimulus features. zitiert von 3
2016
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(2016): A survey of autonomous human affect detection methods for social robots engaged in natural HRI. In: Journal of Intelligent & Robotic Systems 82 (1), S. 101-133. DOI: 10.1007/s10846-015-0259-2
DOI: https://doi.org/10.1007/s10846-015-0259-2 Abstract: In Human-Robot Interactions (HRI), robots should be socially intelligent. They should be able to respond appropriately to human affective and social cues in order to effectively engage in bi-directional communications. Social intelligence would allow a robot to relate to, understand, and interact and share information with people in real-world human-centered environments. This survey paper presents an encompassing review of existing automated affect recognition and classification systems for social robots engaged in various HRI settings. Human-affect detection from facial expressions, body language, voice, and physiological signals are investigated, as well as from a combination of the aforementioned modes. The automated systems are described by their corresponding robotic and HRI applications, the sensors they employ, and the feature detection techniques and affect classification strategies utilized. This paper also discusses pertinent future research directions for promoting the development of socially intelligent robots capable of recognizing, classifying and responding to human affective states during real-time HRI. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Keywords: affect classification models, Affective Valence, automated affect detection, Body language, FACIAL EXPRESSIONS, Human Computer Interaction, human-robot interactions, Mensch-Roboter-Interaktion, Mensch-Technik-Relation, multi-modal, physiological signals, physiology, Social intelligence, Soziale Intelligenz, VOICE 2013
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(2013): Why are you looking like that? How the context influences evaluation and processing of human faces. In: Social cognitive and affective neuroscience 8 (4), S. 438-445. DOI: 10.1093/scan/nss013
DOI: http://www.ncbi.nlm.nih.gov/pubmed/22287265 Abstract: Perception and evaluation of facial expressions are known to be heavily modulated by emotional features of contextual information. Such contextual effects, however, might also be driven by non-emotional aspects of contextual information, an interaction of emotional and non-emotional factors, and by the observers' inherent traits. Therefore, we sought to assess whether contextual information about self-reference in addition to information about valence influences the evaluation and neural processing of neutral faces. Furthermore, we investigated whether social anxiety moderates these effects. In the present functional magnetic resonance imaging (fMRI) study, participants viewed neutral facial expressions preceded by a contextual sentence conveying either positive or negative evaluations about the participant or about somebody else. Contextual influences were reflected in rating and fMRI measures, with strong effects of self-reference on brain activity in the medial prefrontal cortex and right fusiform gyrus. Additionally, social anxiety strongly affected the response to faces conveying negative, self-related evaluations as revealed by the participants' rating patterns and brain activity in cortical midline structures and regions of interest in the left and right middle frontal gyrus. These results suggest that face perception and processing are highly individual processes influenced by emotional and non-emotional aspects of contextual information and further modulated by individual personality traits. zitiert von 56
Keywords: Affective Valence, Amygdala, Brain Mapping, Brain/physiology, Cerebral Blood Flow, Context, Emotions/physiology, Face Perception, Face/physiology, Facial Expression, FACIAL EXPRESSIONS, Female, Functional Magnetic Resonance Imaging, Fusiform Gyrus, Humans, Magnetic Resonance Imaging/methods, Male, Neuroanatomy, Neurowissenschaften, Pattern Recognition, Visual/physiology, Perception/physiology, Personality Traits, Photic Stimulation/methods, Self Reference, social anxiety
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