How to distinguish posed from spontaneous smiles using geometric features
Proceedings of the 9th international conference on Multimodal interfaces
Recognizing Affective Dimensions from Body Posture
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Detecting Affect from Non-stylised Body Motions
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic temporal segment detection and affect recognition from face and body display
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
A Blueprint for Affective Computing: A sourcebook and manual
A Blueprint for Affective Computing: A sourcebook and manual
Modern Applied Statistics with S
Modern Applied Statistics with S
Toward a Minimal Representation of Affective Gestures
IEEE Transactions on Affective Computing
Emotion-Oriented Systems: The Humaine Handbook
Emotion-Oriented Systems: The Humaine Handbook
Gesture-Based affective computing on motion capture data
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Automatic Recognition of Non-Acted Affective Postures
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Near real-time human silhouette and movement detection in indoor environments using fixed cameras
Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
Affective Body Expression Perception and Recognition: A Survey
IEEE Transactions on Affective Computing
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Behavior, including non verbal, expressiveness is an integral part of the communication process since it can provide information on the emotional state and the user's performance when the aim of the interaction is measurable. Long term temporal measurements can also assist in monitoring the user for either emergencies or long term mood instabilities. Current article presents research work on the computational formalization and analysis of full body 3D expressivity in Natural (bodily) Interaction within the framework of Pervasive Assistance. Expressivity dimensions are selected as the most complete approach to body expressivity modeling, since they cover the entire spectrum of expressivity parameters related to emotion and affect. In this study five expressivity parameters are computationally formalized, using different approaches based on silhouette, limbs position and joints rotation, for each expressivity feature. These approaches are then evaluated in terms of their effectiveness in modeling the expressivity aspect in question. The modeling effectiveness of each approach is assessed using Linear Discriminant Analysis (LDA) and its coefficients on the automatically extracted parameters, defined in the computational formalization, against an experimental dataset consisting of extreme expressions (positive and negative) of the investigated expressivity aspects. The The experimental results confirm that the proposed Fading Silhouette Motion Volumes (FMSV) approach, is the most effective in modeling body expressivity.