The DOI matches its Crossref record; 32 of the 34 references it cites were found in a registry or an index.
Automatic analysis of affective postures and body motion to detect engagement with a game companion,
Abstract
The design of an affect recognition system for socially perceptive robots relies on representative data: human-robot interaction in naturalistic settings requires an affect recognition system to be trained and validated with contextualised affective expressions, that is, expressions that emerge in the same interaction scenario of the target application. In this paper we propose an initial computational model to automatically analyse human postures and body motion to detect engagement of children playing chess with an iCat robot that acts as a game companion. Our approach is based on vision-based automatic extraction of expressive postural features from videos capturing the behaviour of the children from a lateral view. An initial evaluation, conducted by training several recognition models with contextualised affective postural expressions, suggests that patterns of postural behaviour can be used to accurately predict the engagement of the children with the robot, thus making our approach suitable for integration into an affect recognition system for a game companion in a real world scenario.
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“The user's body pose can be used to estimate their intent to engage with an embodied agent (Bohus and Horvitz, 2009; Sanghvi et al., 2011; Schwarz et al., 2014).”
From Modeling Feedback in Interaction With Conversational Agents—A Review (2022) · cites this paper as Sanghvi et al., 2011
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Research works printed but not linked: 4
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Metadata
- Authors
- Sanghvi, J., Castellano, G., Leite, I., Pereira, A., McOwan, P. W., & Paiva, A.
- Affiliations
- Queen Mary University of London (GB)
- Instituto Superior Técnico (PT)
- Venue
- Proceedings of the 6th international conference on Human-robot interaction
- Publisher
- ACM
- Published
- 2011-03-06
- Pages
- 305-312
- OpenAlex
- W2105410877
- Cited by
- 250
- References
- 34
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 15 · 2023: 9 · 2022: 25 · 2021: 14 · 2020: 16 · 2019: 26 · 2018: 20 · 2017: 16 · 2016: 26 · 2015: 20 · 2014: 15 · 2013: 20 · 2012: 15
- FWCI
- 26.44
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM/IEEE International Conference on Human-Robot Interaction (HRI) (publishedVersion)
- Funders
- Canadian Institute for Theoretical Astrophysics
- FP7 Information and Communication Technologies
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Social Psychology › Health, Education, and Physical Culture
- Keywords
- affect recognition, human-robot interaction, body motion analysis, chess
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