A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Active Appearance Models Revisited
International Journal of Computer Vision
Deformation transfer for triangle meshes
ACM SIGGRAPH 2004 Papers
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Semantic 3D motion retargeting for facial animation
APGV '06 Proceedings of the 3rd symposium on Applied perception in graphics and visualization
Total Variation Models for Variable Lighting Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial performance capture and expressive translation for King Kong
ACM SIGGRAPH 2006 Sketches
Perception of linear and nonlinear motion properties using a FACS validated 3D facial model
Proceedings of the 7th Symposium on Applied Perception in Graphics and Visualization
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Vertex-Based Diffusion for 3-D Mesh Denoising
IEEE Transactions on Image Processing
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We propose a novel platform to flexibly synthesize any arbitrary meaningful facial expression in the absence of actor performance data for that expression. With techniques from computer graphics, we synthesized random arbitrary dynamic facial expression animations. The synthesis was controlled by parametrically modulating Action Units (AUs) taken from the Facial Action Coding System (FACS). We presented these to human observers and instructed them to categorize the animations according to one of six possible facial expressions. With techniques from human psychophysics, we modeled the internal representation of these expressions for each observer, by extracting from the random noise the perceptually relevant expression parameters. We validated these models of facial expressions with naive observers.