Cited by 234Emotion and Mood RecognitionSocial Robot Interaction and HRIInnovative Human-Technology Interaction

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Affective multimodal human-computer interaction

Pantic, Maja, Sebe, Nicu, Cohn, Jeffrey F., Huang, Thomas·2005·Proceedings of the 13th annual ACM international conference on Multimedia

DOI 10.1145/1101149.1101299

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Abstract

Social and emotional intelligence are aspects of human intelligence that have been argued to be better predictors than IQ for measuring aspects of success in life, especially in social interactions, learning, and adapting to what is important. When it comes to machines, not all of them will need such skills. Yet to have machines like computers, broadcast systems, and cars, capable of adapting to their users and of anticipating their wishes, endowing them with the ability to recognize user's affective states is necessary. This article discusses the components of human affect, how they might be integrated into computers, and how far are we from realizing affective multimodal human-computer interaction.

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Authors: Pantic, M., Sebe, N., Cohn, J. F., & Huang, T.
Affiliations: Delft University of Technology, The Netherlands
University of Amsterdam (NL)
University of Pittsburgh (US)
University of Illinois Urbana-Champaign (US)
ORCID: Sebe, Nicu
Cohn, Jeffrey F.
Huang, Thomas
Venue: Proceedings of the 13th annual ACM international conference on Multimedia
Publisher: ACM
Published: 2005-11-06
Pages: 669-676
DOI: 10.1145/1101149.1101299
OpenAlex: W2028975938
Cited by: 234
References: 50
Citations by year: 2026: 9 · 2025: 11 · 2024: 8 · 2023: 8 · 2022: 23 · 2021: 6 · 2020: 10 · 2019: 9 · 2018: 11 · 2017: 9 · 2016: 7 · 2015: 12 · 2014: 6 · 2013: 14 · 2012: 8
FWCI: 25.50
Type: conference paper
Language: en
Open access: closed
Licence: www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations: ACM International Conference on Multimedia (ACM MM) (publishedVersion)
UvA-DARE (University of Amsterdam) (publishedVersion)
Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
Data Archiving and Networked Services (DANS) (submittedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords: affective computing, multimodal human-computer interaction, affective states, social-emotional intelligence, user modeling, adaptive systems, emotion recognition

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Affective multimodal human-computer interaction

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