Multimodal human discourse: gesture and speech
ACM Transactions on Computer-Human Interaction (TOCHI)
A Gesture Based Interface for Human-Robot Interaction
Autonomous Robots
Non-obvious Performer Gestures in Instrumental Music
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Multimodal model integration for sentence unit detection
Proceedings of the 6th international conference on Multimodal interfaces
Children's intuitive gestures in vision-based action games
Communications of the ACM - Interaction design and children
The catchment feature model: a device for multimodal fusion and a bridge between signal and sense
EURASIP Journal on Applied Signal Processing
Gesture recognition in flow based on PCA analysis using multiagent system
ACE '08 Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology
Human-inspired search for redundancy in automatic sign language recognition
ACM Transactions on Applied Perception (TAP)
Recognition of gesture sequences in real-time flow, context of virtual theater
GW'09 Proceedings of the 8th international conference on Gesture in Embodied Communication and Human-Computer Interaction
Gesture unit segmentation using support vector machines: segmenting gestures from rest positions
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Guest Editorial: Gesture and speech in interaction: An overview
Speech Communication
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A method for the recovery of the temporal structure and phases in natural gesture is presented. The work is motivated by recent developments in the theory of natural gesture which have identified several key aspects of gesture important to communication. In particular, gesticulation during conversation can be coarsely characterized as periods of bi-phasic or tri-phasic gesture separated by a rest state. We first present an automatic procedure for hypothesizing plausible rest state configurations of a speaker; the method uses the repetition of subsequences to indicate potential rest states. Second, we develop a state-based parsing algorithm used to both select among candidate rest states and to parse an incoming video stream into bi-phasic and multi-phasic gestures. We present results from examples of story-telling speakers.