Computer Animation and Virtual Worlds - Special Issue: The Very Best Papers from CASA 2004
Does Body Movement Engage You More in Digital Game Play? and Why?
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Using Actor Portrayals to Systematically Study Multimodal Emotion Expression: The GEMEP Corpus
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
ICDHM '09 Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009
Combining Facial and Postural Expressions of Emotions in a Virtual Character
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Augmenting Gesture Animation with Motion Capture Data to Provide Full-Body Engagement
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Towards a common framework for multimodal generation: the behavior markup language
IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents
Expressive body animation pipeline for virtual agent
IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
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One of the challenges of virtual character research is the specification of reliable and discriminative features of complex emotions in multiple modalities. Whereas expressions of different emotion categories in facial expressions, gaze, and gestures were explored in several studies, postural expressions of emotion and other components of emotions received less attention. In this paper, we propose an approach for designing and evaluating postural expressions of action tendencies. We designed postural expressions of several action tendencies using MARC, our virtual character animation platform. These postures were informed by data from the literature completed with the manual annotations of an exploratory video corpus. A decoding study tested 5 pairs of static pictures of postural expressions in terms of action tendencies as well as discrete emotion categories. Subjects reliably recognized the postural expressions of the following action tendencies: attending, disappear from view and exuberant. Perception of emotion categories was also consistent with psychological predictions about action tendencies. These results suggest that postural expressions can be useful to express action tendencies in virtual characters.