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Article dans une revue

Emotional Valence Recognition on Virtual, Robotic, and Human Faces: a Comparative Study

Abstract : With the advent of new technologies in everyday life, leisure, or therapy, we will increasingly interact with a non-human virtual character. Understanding facial expressions and intentions of these virtual agents is important to enable them to achieve their goals. The objective of our study is to assess whether expressions are perceived as being positive or negative on faces more or less similar to those of humans. Eighty-three undergraduate students took part in a computerized emotion recognition task. The participants had to identify whether each face expressed a positive or a negative emotion. Eight different faces (human, avatar, mesh, and robot) were shown 38 times each on a computer screen. Each face was represented by a photo. Response time and the number of correct responses were recorded. Our research has raised important points: the accuracy and time taken for emotion recognition were found to be similar on human or avatar faces. On the other hand, as soon as these faces were too ambiguous or schematic, emotion recognition capacities were found to be diminished.
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Article dans une revue
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Contributeur : Jonathan Del-Monte <>
Soumis le : mardi 16 mars 2021 - 17:23:04
Dernière modification le : samedi 20 mars 2021 - 03:26:42
Archivage à long terme le : : jeudi 17 juin 2021 - 19:57:21


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Lisa Cerda, Pierluigi Graziani, Jonathan Del-Monte. Emotional Valence Recognition on Virtual, Robotic, and Human Faces: a Comparative Study. Journal of Technology in Behavioral Science, Springer, 2021, 6 (1), pp.151 - 158. ⟨10.1007/s41347-020-00172-5⟩. ⟨hal-03171138⟩



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