The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Toward a Minimal Representation of Affective Gestures
Open accessAbstract
This paper presents a framework for analysis of affective behavior starting with a reduced amount of visual information related to human upper-body movements. The main goal is to individuate a minimal representation of emotional displays based on nonverbal gesture features. The GEMEP (Geneva multimodal emotion portrayals) corpus was used to validate this framework. Twelve emotions expressed by 10 actors form the selected data set of emotion portrayals. Visual tracking of trajectories of head and hands were performed from a frontal and a lateral view. Postural/shape and dynamic expressive gesture features were identified and analyzed. A feature reduction procedure was carried out, resulting in a 4D model of emotion expression that effectively classified/grouped emotions according to their valence (positive, negative) and arousal (high, low). These results show that emotionally relevant information can be detected/measured/obtained from the dynamic qualities of gesture. The framework was implemented as software modules (plug-ins) extending the EyesWeb XMI Expressive Gesture Processing Library and is going to be used in user centric, networked media applications, including future mobiles, characterized by low computational resources, and limited sensor systems.
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Cites
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Cited by
Affective Body Expression Perception and Recognition: A Survey
Kleinsmith, A., & Bianchi-Berthouze, N. (2013) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2012.16 · Cited by 607
Survey on Emotional Body Gesture Recognition
Noroozi, F., Corneanu, C. A., Kaminska, D., Sapinski, T., Escalera, S., & Anbarjafari, G. (2021) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2874986 · Cited by 455
Gunes, H., & Schuller, B. (2013) · Image and Vision Computing · doi:10.1016/j.imavis.2012.06.016 · Cited by 360
Emotion Recognition for Human-Robot Interaction: Recent Advances and Future Perspectives
Spezialetti, M., Placidi, G., & Rossi, S. (2020) · Frontiers in Robotics and AI · doi:10.3389/frobt.2020.532279 · Cited by 293
Khezri, M., Firoozabadi, M., & Sharafat, A. R. (2015) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2015.07.006 · Cited by 89
Metadata
- Authors
- Glowinski, D., Dael, N., Camurri, A., Volpe, G., Mortillaro, M., & Scherer, K.
- Venue
- IEEE Transactions on Affective Computing
- Published
- 2011-04
- Volume
- 2
- Issue
- 2
- Pages
- 106-118
- ISSN
- 1949-3045 (ISSN-L)
- OpenAlex
- W2106508100
- Cited by
- 215
- References
- 12
- FWCI
- 18.98
- Type
- journal article
- Language
- en
- Open access
- green
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