Animating blendshape faces by cross-mapping motion capture data
I3D '06 Proceedings of the 2006 symposium on Interactive 3D graphics and games
Expressive Facial Animation Synthesis by Learning Speech Coarticulation and Expression Spaces
IEEE Transactions on Visualization and Computer Graphics
eFASE: expressive facial animation synthesis and editing with phoneme-isomap controls
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Interactive 3D facial expression posing through 2D portrait manipulation
GI '08 Proceedings of graphics interface 2008
A model of gaze for the purpose of emotional expression in virtual embodied agents
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Towards Natural Head Movement of Autonomous Speaker Agent
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Decimation of human face model for real-time animation in intelligent multimedia systems
Multimedia Tools and Applications
On the importance of eye gaze in a face-to-face collaborative task
Proceedings of the 3rd international workshop on Affective interaction in natural environments
Mood avatar: automatic text-driven head motion synthesis
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Speech, gaze and head motion in a face-to-face collaborative task
Proceedings of the Third COST 2102 international training school conference on Toward autonomous, adaptive, and context-aware multimodal interfaces: theoretical and practical issues
Perceptual analysis of talking avatar head movements: a quantitative perspective
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Perceiving visual emotions with speech
IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents
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Natural head motion is important to realistic facial animation and engaging human–computer interactions. In this paper, we present a novel data-driven approach to synthesize appropriate head motion by sampling from trained hidden markov models (HMMs). First, while an actress recited a corpus specifically designed to elicit various emotions, her 3D head motion was captured and further processed to construct a head motion database that included synchronized speech information. Then, an HMM for each discrete head motion representation (derived directly from data using vector quantization) was created by using acoustic prosodic features derived from speech. Finally, first-order Markov models and interpolation techniques were used to smooth the synthesized sequence. Our comparison experiments and novel synthesis results show that synthesized head motions follow the temporal dynamic behavior of real human subjects. Copyright © 2005 John Wiley & Sons, Ltd.