The SVD and reduced rank signal processing
Signal Processing - Theme issue on singular value decomposition
Principal component neural networks: theory and applications
Principal component neural networks: theory and applications
Computer facial animation
Expressive expression mapping with ratio images
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Creating Interactive Virtual Humans: Some Assembly Required
IEEE Intelligent Systems
Multilinear Analysis of Image Ensembles: TensorFaces
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Real-Time Facial Animation based upon a Bank of 3D Facial Expressions
CA '98 Proceedings of the Computer Animation
An example-based approach for facial expression cloning
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Vision-based control of 3D facial animation
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Facial Expression Decomposition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Face transfer with multilinear models
ACM SIGGRAPH 2005 Papers
Geometry-Driven Photorealistic Facial Expression Synthesis
IEEE Transactions on Visualization and Computer Graphics
Separating Style and Content with Bilinear Models
Neural Computation
Manifold based analysis of facial expression
Image and Vision Computing
Synthesis and recognition of facial expressions in virtual 3D views
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A realistic dynamic facial expression transfer method
Neurocomputing
Facial action transfer with personalized bilinear regression
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
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In the last few years, Facial Expression Synthesis (FES) has been a flourishing area of research driven by applications in character animation, computer games, and human computer interaction. This paper proposes a photorealistic FES method based on Bilinear Kernel Reduced Rank Regression (BKRRR). BKRRR learns a high-dimensional mapping between the appearance of a neutral face and a variety of expressions (e.g. smile, surprise, squint). There are two main contributions in this paper: (1) Propose BKRRR for FES. Several algorithms for learning the parameters of BKRRR are evaluated. (2) Propose a new method to preserve subtle person-specific facial characteristics (e.g. wrinkles, pimples). Experimental results on the CMUMulti-PIE database and pictures taken with a regular camera show the effectiveness of our approach.