A Numerical Solution to the Generalized Mapmaker's Problem: Flattening Nonconvex Polyhedral Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Three-Frame Algorithm for Estimating Two-Component Image Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing Images under Variable Illumination
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
Data Fusion and Multicue Data Matching by Diffusion Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Manifold models for signals and images
Computer Vision and Image Understanding
Nonlinear Dimensionality Reduction by Topologically Constrained Isometric Embedding
International Journal of Computer Vision
Ethnicity- and Gender-based Subject Retrieval Using 3-D Face-Recognition Techniques
International Journal of Computer Vision
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Understanding facial expressions in image sequences is an easy task for humans. Some of us are capable of lipreading by interpreting the motion of the mouth. Automatic lipreading by a computer is a challenging task, with so far limited success. The inverse problem of synthesizing real looking lip movements is also highly non-trivial. Today, the technology to automatically generate an image series that imitates natural postures is far from perfect.We introduce a new framework for facial image representation, analysis and synthesis, in which we focus just on the lower half of the face, specifically the mouth. It includes interpretation and classification of facial expressions and visual speech recognition, as well as a synthesis procedure of facial expressions that yields natural looking mouth movements.Our image analysis and synthesis processes are based on a parametrization of the mouth configuration set of images. These images are represented as points on a two-dimensional flat manifold that enables us to efficiently define the pronunciation of each word and thereby analyze or synthesize the motion of the lips. We present some examples of automatic lips motion synthesis and lipreading, and propose a generalization of our solution to the problem of lipreading different subjects.