Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners

Hatice Gunes; Maja Pantic

doi:10.1007/978-3-642-15892-6_39

Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners

Hatice Gunes, Maja Pantic

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

56 Citations (Scopus)

Abstract

This paper focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [1] that aims to achieve sustained emotionally-colored interaction between a human user and Sensitive Artificial Listeners

Original language	Undefined
Title of host publication	Proceedings of the 10th International Conference on Intelligent Virtual Agents, IVA 2010
Editors	Jan Allbeck, Norman Badler, Timothy Bickmore, Catherine Pelachaud, Alla Safonova
Place of Publication	Berlin
Publisher	Springer
Pages	371-377
Number of pages	7
ISBN (Print)	978-3-642-15892-6
DOIs	https://doi.org/10.1007/978-3-642-15892-6_39 https://doi.org/10.1007/978-3-642-15892-6
Publication status	Published - 21 Sep 2010
Event	10th International Conference on Intelligent Virtual Agents, IVA 2010 - Philadelphia, United States Duration: 20 Sep 2010 → 22 Sep 2010 Conference number: 10

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	6356

Conference

Conference	10th International Conference on Intelligent Virtual Agents, IVA 2010
Abbreviated title	IVA
Country	United States
City	Philadelphia
Period	20/09/10 → 22/09/10

Keywords

IR-75933
METIS-275891
Spontaneous head movements
HMI-MI: MULTIMODAL INTERACTIONS
virtual character-human interaction
EWI-19479
dimensional emotion prediction
EC Grant Agreement nr.: FP7/211486

Access to Document

http://eprints.eemcs.utwente.nl/secure2/19479/01/pantic_dimensional_emotion_prediction_from.pdf

Cite this

Gunes, H., & Pantic, M. (2010). Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners. In J. Allbeck, N. Badler, T. Bickmore, C. Pelachaud, & A. Safonova (Eds.), Proceedings of the 10th International Conference on Intelligent Virtual Agents, IVA 2010 (pp. 371-377). (Lecture Notes in Computer Science; Vol. 6356). Springer. https://doi.org/10.1007/978-3-642-15892-6_39, https://doi.org/10.1007/978-3-642-15892-6

Gunes, Hatice ; Pantic, Maja. / Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners. Proceedings of the 10th International Conference on Intelligent Virtual Agents, IVA 2010. editor / Jan Allbeck ; Norman Badler ; Timothy Bickmore ; Catherine Pelachaud ; Alla Safonova. Berlin : Springer, 2010. pp. 371-377 (Lecture Notes in Computer Science).

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title = "Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners",

abstract = "This paper focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [1] that aims to achieve sustained emotionally-colored interaction between a human user and Sensitive Artificial Listeners",

keywords = "IR-75933, METIS-275891, Spontaneous head movements, HMI-MI: MULTIMODAL INTERACTIONS, virtual character-human interaction, EWI-19479, dimensional emotion prediction, EC Grant Agreement nr.: FP7/211486",

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Gunes, H & Pantic, M 2010, Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners. in J Allbeck, N Badler, T Bickmore, C Pelachaud & A Safonova (eds), Proceedings of the 10th International Conference on Intelligent Virtual Agents, IVA 2010. Lecture Notes in Computer Science, vol. 6356, Springer, Berlin, pp. 371-377, 10th International Conference on Intelligent Virtual Agents, IVA 2010, Philadelphia, United States, 20/09/10. https://doi.org/10.1007/978-3-642-15892-6_39, https://doi.org/10.1007/978-3-642-15892-6

Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners. / Gunes, Hatice; Pantic, Maja.

Proceedings of the 10th International Conference on Intelligent Virtual Agents, IVA 2010. ed. / Jan Allbeck; Norman Badler; Timothy Bickmore; Catherine Pelachaud; Alla Safonova. Berlin : Springer, 2010. p. 371-377 (Lecture Notes in Computer Science; Vol. 6356).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - This paper focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [1] that aims to achieve sustained emotionally-colored interaction between a human user and Sensitive Artificial Listeners

AB - This paper focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [1] that aims to achieve sustained emotionally-colored interaction between a human user and Sensitive Artificial Listeners

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KW - HMI-MI: MULTIMODAL INTERACTIONS

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KW - EWI-19479

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PB - Springer

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Gunes H, Pantic M. Dimensional Emotion Recognition from Spontaneous Head Gestures for Interaction with Sensitive Artificial Listeners. In Allbeck J, Badler N, Bickmore T, Pelachaud C, Safonova A, editors, Proceedings of the 10th International Conference on Intelligent Virtual Agents, IVA 2010. Berlin: Springer. 2010. p. 371-377. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-15892-6_39, https://doi.org/10.1007/978-3-642-15892-6