We present AMHUSE (A Multimodal dataset for HUmour SEnsing) along with a novel web-based annotation tool named DANTE (Di- mensional ANnotation Tool for Emotions). The dataset is the result of an experiment concerning amusement elicitation, involving 36 subjects in order to record the reactions in presence of 3 amusing and 1 neutral video stimuli. Gathered data include RGB video and depth sequences along with physiological responses (electrodermal activity, blood volume pulse, temperature). The videos were later annotated by 4 experts in terms of valence and arousal continuous dimensions. Both the dataset and the annotation tool are made publicly available for research purposes.

AMHUSE: A Multimodal dataset for HUmour SEnsing / Boccignone, G.; Donatello, Conte; Cuculo, V.; Lanzarotti, R.. - 2017-:(2017), pp. 438-445. (Intervento presentato al convegno 19th ACM International Conference on Multimodal Interaction, ICMI 2017 tenutosi a Glasgow nel 2017) [10.1145/3136755.3136806].

AMHUSE: A Multimodal dataset for HUmour SEnsing

V. Cuculo;
2017

Abstract

We present AMHUSE (A Multimodal dataset for HUmour SEnsing) along with a novel web-based annotation tool named DANTE (Di- mensional ANnotation Tool for Emotions). The dataset is the result of an experiment concerning amusement elicitation, involving 36 subjects in order to record the reactions in presence of 3 amusing and 1 neutral video stimuli. Gathered data include RGB video and depth sequences along with physiological responses (electrodermal activity, blood volume pulse, temperature). The videos were later annotated by 4 experts in terms of valence and arousal continuous dimensions. Both the dataset and the annotation tool are made publicly available for research purposes.
2017
19th ACM International Conference on Multimodal Interaction, ICMI 2017
Glasgow
2017
2017-
438
445
Boccignone, G.; Donatello, Conte; Cuculo, V.; Lanzarotti, R.
AMHUSE: A Multimodal dataset for HUmour SEnsing / Boccignone, G.; Donatello, Conte; Cuculo, V.; Lanzarotti, R.. - 2017-:(2017), pp. 438-445. (Intervento presentato al convegno 19th ACM International Conference on Multimodal Interaction, ICMI 2017 tenutosi a Glasgow nel 2017) [10.1145/3136755.3136806].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1300649
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