Probabilistic Combination of Multiple Modalities to Detect Interest
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Computer Animation and Virtual Worlds - Special Issue: The Very Best Papers from CASA 2004
Cross-cultural differences in recognizing affect from body posture
Interacting with Computers
Towards unsupervised detection of affective body posture nuances
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Grounding affective dimensions into posture features
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Combining Facial and Postural Expressions of Emotions in a Virtual Character
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Automatic measurement of affect in dimensional and continuous spaces: why, what, and how?
Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research
Evaluating multimodal affective fusion using physiological signals
Proceedings of the 16th international conference on Intelligent user interfaces
Multimodal behavior realization for embodied conversational agents
Multimedia Tools and Applications
Improving a method for quantifying readers' impressions of news articles with a regression equation
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Smart solutions for risk prevention through analysis of people movements
GPC'11 Proceedings of the 6th international conference on Grid and Pervasive Computing
Expressive body animation pipeline for virtual agent
IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
Image and Vision Computing
Comparing four technologies for measuring postural micromovements during monitor engagement
Proceedings of the 30th European Conference on Cognitive Ergonomics
Proceedings of the 2013 international conference on Intelligent user interfaces
Natural interaction expressivity modeling and analysis
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
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The recognition of affective human communication may be used to provide developers with a rich source of information for creating systems that are capable of interacting well with humans. Posture has been acknowledged as an important modality of affective communication in many fields. Behavioral studies have shown that posture can communicate discrete emotion categories as well as affective dimensions. In the affective computing field, while models for the automatic recognition of discrete emotion categories from posture have been proposed, to our knowledge, there are no models for the automatic recognition of affective dimensions from static posture. As a continuation of our previous study, the two main goals of this study are: i) to build automatic recognition models to discriminate between levels of affective dimensions based on low-level postural features; and ii) to investigate both the discriminative power and the limitations of the postural features proposed. The models were built on the basis of human observers' ratings of posture according to affective dimensions directly (instead of emotion category) in conjunction with our posture features.