Sciweavers

Share
IVC
2006

Manifold based analysis of facial expression

11 years 5 months ago
Manifold based analysis of facial expression
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embedding. In this space, facial contour features are first clustered, using a mixture model. Then, expression dynamics are learned for tracking and classification. We use ICondensation to track facial features in the embedded space, while recognizing facial expressions in a cooperative manner, within a common probabilistic framework. The image observation likelihood is derived from a variation of the Active Shape Model (ASM) algorithm. For each cluster in the lowdimensional space, a specific ASM model is learned, thus avoiding incorrect matching due to non-linear image variations. Preliminary experimental results show that our probabilistic facial expression model on manifold significantly improves facial deformation tracking and expression recognition.
Ya Chang, Changbo Hu, Rogerio Feris, Matthew Turk
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where IVC
Authors Ya Chang, Changbo Hu, Rogerio Feris, Matthew Turk
Comments (0)
books